Inria - Strategic plan 2008-2012

INRIA

Strategic Plan

2008 - 2012

Contents

1 INRIA: A Brief History1.1 FromInceptiontotheLate1990s page6

1.2 1999-2003:UnprecedentedGrowth page8

1.3 2004-2007:ConsolidationandNewGrowth page10

2 ICST Research: Context and Key Issues2.1 SocietalIssues page28

2.2 ScientificandTechnologicalChallenges page31

2.3 TheInternationalandNationalFramework

forICSTResearch page33

3INRIA: Strategic Priorities and Ambitions3.1 Modeling,Programming,Communicating andInteracting page41

3.1.1 Modeling,SimulationandOptimizationofComplexDynamicSystems page42

3.1.2 Programming:securityandreliabilityofcomputingsystems page48

3.1.3 Information,ComputationandCommunicationEverywhere page56

3.1.4 InteractionwithRealandVirtualWorlds page64

3.2 ComputationalSciencesandEngineering page71

3.2.2 ComputationalSciences page78

3.2.3 ComputationalMedicine page88

3.3 SocialConcernsCoveredbyINRIAPriorities page93

3.4 EmergingFields page95

4Actions and Strategy for Achieving the Objectives4.1 INRIA’sRoleinFrance page98

4.2 ImprovingtheInstitute’sAttractiveness page100

4.3 Research,DevelopmentandTransfer page110

4.4 EuropeanandInternationalRelations page118

4.5 InternalOrganizationandOperation page120

Glossary page124

�Strategic Plan 2008-2012

H istory

Inthischapter:

INRIA: A Brief History

1.1 FromInceptiontotheLate1990s page6

1.2 1999-2003:UnprecedentedGrowth page8

1.3 2004-2007:ConsolidationandNewGrowth page10

H istory

� Strategic Plan 2008-2012

From Inception to the Late 1990s

1.1

Jacques-Louis Lions - 1980. * A list of acronyms can be found in the appendix.

INRIA’s strategy for the coming years draws on its history, and in particular the strong growth dynamic that developed in the early 2000s.

IRIA, the French institute for computer science and automatic control research, was founded in 19�7 at Rocquencourt, near Versailles, as part of the “Computer Development Plan” designed to improve French computer science research and the industry. It was renamed INRIA in 1979 and gained the status of EPST* (public scientific and technological establishment) in 1985.Most of the foundational work was carried out by Jacques-Louis Lions, who performed research in applied mathematics at IRIA starting in 19�7 and became the first chairman of INRIA, from 1979 until 1984. He was not only one of the grea-test applied mathematicians of the 20th century,

but also a visionary who, as early as the 1950s, understood that the advent of computers would lead to major advances in applied mathematics and computer science. Several aspects of the rich heritage left by Jacques-Louis Lions are still in evidence at INRIA today:• a research institute combining computer

science, automatic control and applied mathe-matics within a single institution, where they interact with each other in depth;

• a positive vision of industrial relations as a source of promising new research questions;

• a structure based on teams of 10-20 resear-chers sharing common goals, called “research project-teams”, without any intermediate, department-like structure;

• special attention paid to training, particularly doctoral training, in close cooperation with universities and engineering schools;

• strong involvement in international cooperation.

Alain Bensoussan, automatic control specialist, professor at the University of Paris-Dauphine and former colleague of Jacques-Louis Lions, succeeded the latter as chairman of INRIA from 1984 to 199�. Bensoussan continued in the same vein as his predecessor, consolidating INRIA’s reputation in Europe and worldwide. The Institute played a pioneering role in introducing the Internet in France and supporting the creation of companies as early as 1984: 25 companies were launched between 1984 and 1994, including Ilog, a world leader in software components for optimization. INRIA became heavily involved in consolidating European Research Area, in particular by creating the ERCIM Consortium in Germany, founded in 1989 with the GMD, and the CWI in the Netherlands. In 1995, INRIA was chosen by MIT and the European Commission to be the European host for the World Wide Web Consortium (W�C), the web standards body.During the same period, INRIA developed major partnerships with French research orga-nizations and universities. New research units were created : the first one on the Rennes University campus in 1980, followed by one in 198� in the brand new Sophia-Antipolis techno-logy cluster near Nice and still another in Lorraine in 198� on the Nancy University campus. The fifth research unit, Rhône-Alpes, was opened in Grenoble in 1992, with a branch in Lyon.

1.1 From Inception to the Late 1990s

History

7Strategic Plan 2008-2012

In 1994, INRIA issued its first Strategic Plan, which emphasized the role of information and communication science and technology (ICST) in disseminating information, as well as the importance of applications and industrial rela-tions, and introduced the motto reflecting the Institute’s strategic goals: scientific excellence and technology transfer. The plan energized INRIA and its staff to develop activities capi-talizing on research, as can be seen from the fact that the Institute’s resources for research contracts doubled between 1994 and 1999, whereas the permanent workforce increased by barely 10%. This was also a period of major external change, with the “convergence” of computing, telecommunications and audiovisual technology, the deregulation of telecommunica-tions, and the rapid growth of the Internet and information and communication technology. In keeping with these changes, INRIA significantly redirected its research efforts and began to focus on communications, especially on Internet and web technologies and network modeling. At the same time, the Institute actively continued its work in the field of medical technology, which had been developing gradually since the early 1990s.During the period from 1984-199�, several aspects of INRIA’s internal policy were re-emphasized:• the Institute improved the quality and rigor of

the research project-team assessment process and encouraged researchers to create new project-teams and take on more leadership roles within them;

• it increased its efforts to support the creation of companies;

• it promoted openness by strongly encouraging mobility for researchers and engineers and by recruiting more widely from the pool of external candidates;

• INRIA expanded its partnerships with French research organizations by developing more projects jointly with other establishments and by launching the highly successful concept of “cooperative research initiatives,” which were open to external teams, to develop new joint efforts and address original research topics.

During this period, however, the Institute also encountered some serious problems. These difficulties were linked in part to the unfavorable economic context and the heavy constraints on the State budget, which made it very difficult to expand the two most recent research units in

Lorraine and Rhône-Alpes. The Institute’s work in general suffered from the lack of research support staff (engineers, technicians and admi-nistrative personnel) needed to support research adequately. The situation was further complicated by the fact that CNRS and university research departments had to start signing contracts with the Ministry for their funding around 1995-199�. This new development created tension between INRIA and these establishments, because it was difficult to reconcile the Institute’s organization into small teams with organizations based on departments.

8 Strategic Plan 2008-2012

1999-2003: Unprecedented

Growth

1.2

Object tracking — MAIA.

Bernard Larrouturou, applied mathematician and professor at the Ecole Polytechnique, was appointed president of INRIA in 199�. From 1997 onward, INRIA increased its efforts to advocate the strategic importance of information and communication science and technology (ICST) in France and throughout Europe. In 1999, the Institute adopted an ambitious new strategic plan, strongly urging that ICST be given a clear priority in the national research policy. The plan also stated INRIA’s resolve to consolidate its leading role within the national program and its ambition to play a more active role in the fierce international competition in ICST, aiming to be recognized within a few years as the European leader and one of the best research centers in its field worldwide.

A Top Priority for Government Authorities2000 was a pivotal year: the Interministerial Council for the Information Society held on July 10, 2000 and chaired by the prime minister noted that the strategic plan drafted by INRIA the year before had been a determining factor in defining an ambitious national ICST policy, and it announced a significant increase in government research efforts in the field. The prime minister agreed to double the Institute’s resources over a ten-year period, and announced the signing of the 2000-200�

four-year contract, which called for increasing the number of government-funded positions at INRIA from 7�� in 2000 to 1,100 and 80 fixed-term contracts in 200�. Receiving such a high priority despite the budget constraints on funding for research over the following years meant that by 200�, INRIA had 1,148 state-funded positions: 1,0�1 permanent positions and 117 fixed term contracts.

An Institute in the Thick of International CompetitionThe Institute considerably stepped up its efforts to attract more foreign research scientists, aiming to become far more international in scope: one-third of the permanent research scientists recruited by INRIA between 2001 and 200� were not of French nationality. In addi-tion, the Institute greatly expanded its visiting researcher policy, reserving approximately one-third of all positions created for visiting professors and civil servants from French government technical bodies. Fixed-term contracts were also offered to recent enginee-ring graduates to offer them a highly technical experience as they entered the working world. In cooperation with partner universities and engineering schools, INRIA strove to increase the number of PhD students on research project-teams. This number rose from 5�0 to 750 between the first half of 2000 and the first half of 200�; one-third of the students were foreigners.There were many indicators that INRIA’s inter-national influence was expanding rapidly: more articles published in international jour-nals with greater impact, over and above the increase in staff; more foreign visitors, especially from Asia and all across Europe; the Institute’s heavy involvement in the fifth European Union Framework Program (FP), where it was much more involved than in the fourth FP; and the increasing renown of the ERCIM consortium, led by INRIA and serving as European host for the W�C in 200�, on the Institute’s initiative. Many observers began to see the institute as one of the leading European research centers in its field.A strategic assessment committee made up almost exclusively of well-known figures from abroad – the Visiting Committee – met for the first time in 2002 to assess the work of the Institute’s management and evaluate

1.2 1999-200�: Unprecedented Growth

History


INRIA’s commitment to focus its efforts on high-priority subjects also affected its work on technology transfer.

INRIA as a whole . Finally, the 200� overhaul of INRIA’s scientific council provided the oppor-tunity to give the board a clearly European composition.

Stronger National Partnerships and LeadershipIn France, INRIA expanded its partnerships with higher-education establishments. In 200�, almost two-thirds of the Institute’s research projects were joint projects with such establis-hments – roughly twice as many as in 1999. The development plan approved by the Board of Directors called for opening three new research units over the long term in the southwest and the north of France and on the Saclay plateau. On January 1, 2002, the Institute decided to create a virtual sixth research unit called Futurs, based on the Bordeaux, Lille and Saclay sites, to serve as an incubator for the new units and assist in integrating them into the internal struc-ture of INRIA.At the same time, the Institute implemented a geographical expansion policy for each of the five older research units: in 200�, there were around fifteen “off-site” project-teams in Besançon, Cachan, Lannion, Marne-la-Vallée, Marseille, Metz, Paris and Lyon.

Clear Scientific PolicyIn light of the government’s priorities, the Institute devoted itself to focusing on the following five high-priority goals :• mastering the digital infrastructure by being able

to program, compute and communicate over the Internet and heterogeneous networks;

• designing new applications using the Web and multimedia databases;

• knowing how to produce reliable software;• designing and mastering automatic control for

complex systems;• combining simulation and virtual reality;It also emphasized two major fields of application:• telecommunications and multimedia;• health and biology.This subject-specific focus significantly influenced the dynamic of INRIA’s scien-tific work. In particular, for the first two scien-

tific golas and the first field of application, the Institute considerably expanded its research on telecommunications networks (broadband networks, mobiles, wireless, ad hoc), multimedia data transport and processing, middleware development for distributed computing and grid computing. In addition, the fields of health and biology were far more successful than expected, making substantial advances in bioinformatics, medical technology and neurosciences.INRIA’s commitment to focus its efforts on high-priority subjects also affected its work on technology transfer. Despite economic diffi-culties, the telecommunications sector stood out as the prime industrial field to which INRIA research contributed, and it developed close partnerships with leading European and inter-national companies, including Alcatel, France Telecom, Hitachi and Philips. The Institute’s industrial relationships in France, especially with SMEs, expanded through its involvement with the national research and technological innovation networks set up by the government. INRIA and its subsidiary INRIA-Transfert, founded in 1998 to act as incubator and set up the very first funds, reso-lutely pursued their start-up support activities. The number of companies incubated at INRIA topped �0. Based on its experience with the W�C, the Institute encouraged the creation of consortiums with academic and industrial partners to share development efforts and increase the chances of success for several open-source software packages arising from INRIA research, such as Scilab and ObjectWeb.

Internal Weak PointsSuch rapid growth − approximately 50% over three years − inevitably came with many internal changes that were sometimes difficult to control. INRIA was faced with a large number of new issues concerning its organization, human resources policy, managerial practices and admi-nistrative management. Human resources policy showed the clearest progress, while the greatest difficulties were encountered in administrative and financial management, mainly because the support staff was not sufficiently increased in proportion to administrative tasks; manage-ment software tools were inappropriate and the project, launched in 2001, to replace them with an integrated information system was delayed; and lastly, management control procedures were not sufficiently developed.

* The recommendations of the Visiting Committee played a major role in drafting the next Strategic Plan.


2004-2007: Consolidation and

New Growth

1.3 In late 200�, Michel Cosnard, a computer scientist and professor at the University of Nice -Sophia Antipolis was appointed chairman of the Institute, followed from 2004-200� by Gilles Kahn, a computer scientist and research director at INRIA, who was chairman until his death in early 200�. Michel Cosnard took over from Kahn in mid-200�.The 2004-2007 strategic plan, approved by the board of trustees in July 200�, confirmed the Institute’s resolve to be recognized as the leading European research center and one of the best in the world in the fields of computer science, automatic control and applied mathematics. To fulfill this ambition, the Institute defined a policy based on clearly stated choices.

INRIA’s Seven Scientific and Technological ObjectivesICST innovation is essentially based on scientific research, sometimes at the most fundamental level. The 2004-2007 strategic plan confirmed this priority, closely tying together scientific excellence and techno-logy transfer. INRIA is, however, fully aware that it cannot cover all the research topics in this vast field of science and techno-logy, given that the scope of its applications and depth of interaction with other fields is continuously increasing. This demands making choices in scientific and techno-logical policy. INRIA has set its priorities according to the skills available to it and the Institute’s appraisal of scientific, technolo-gical, economic and social objectives. INRIA’s main goal for the period covered by the 2004-2007 strategic plan was to make major scientific and technolo-gical breakthroughs in keeping with the following seven objectives:• designing and mastering future infrastructures

for networks and communication services;• developing information and multimedia

processing;• guaranteeing the reliability and security of

intensive software systems;• connecting models and data to simulate

and master complex systems;• combining simulation, visualization and

interaction;• modeling living systems;• fully integrating ICST into medical technology.

As of the end of 200�, these objectives collec-tively represented over 75% of the efforts of research project-teams, with the last two alone accounting for over 15%. The trend towards life and health sciences and medical techno-logy has been reflected in the research projects themselves: there are now more than 500 research scientists working in these areas.

Creating Excellence ClustersINRIA is the only French national research esta-blishment exclusively dedicated to computer science, automatic control and applied mathe-matics. The quality of its research scientists, its involvement in training through research and its results in both research and technology transfer, along with its definite commitment to building the European Research Area and international competition, now make INRIA the most internationally visible French research body in the field.Working closely with higher education organizations, INRIA is continuing to develop its research units, which play a leading role at the sites where they are located, aiming to establish them as European and international excellence clusters. The number of INRIA projects shared with higher education esta-blishments or research organizations rose from 80 as of January 1, 2004 to 111 as of January 1, 2007. INRIA’s visiting researcher policy plays an important role in this respect. In 200� and 2007, over 50 research scientist positions were reserved for research profes-sors and research scientists on temporary assignments from other organizations, in particular from other scientific fields, giving priority to life sciences. For the same period, approximately 55 research professors were sent on assignments elsewhere.To prepare for the launch of INRIA research units in Bordeaux, Lille and Saclay on January 1, 2008, many of the additional and redeployed resources were allocated to Futurs, with staff increasing from 2�� as of January 1, 2004 to �12 as of January 1, 2007.

Research OrganizationDuring this period, in order to more effecti-vely reflect the national ICST research policy, INRIA underwent a complete re-organization: positions were created for a chief officer for science and technology and a chief officer

1.� 2004-2007: Consolidation and New Growth

History


Working closely with higher education organizations, INRIA is continuing to develop its research units, which play a leading role at the sites where they are located, aiming to establish them as European and international excellence clusters.

for resources and administration; the scien-tific and operational departments were reor-ganized; positions were created for deputy scientific directors and scientific advisors; the research units were renamed “INRIA Research Centers and research project were renamed “INRIA Project-Teams” (IPT), most of which were shared with other partners; the role of research center directors was clearly defined; and the project committee chairman was renamed “scientific officer”.Research organization at INRIA continues to be based mainly on IPTs. The visibility and impact of the work carried out in the Institute has been increased by promoting the collective aspect of research and by gathering research scientists into teams with clearly identified goals. This organizational struc-ture allows for a great deal of flexibility and responsiveness as it ensures that IPTs exist only for a limited time and are able to evolve and change directions. The number of IPTs increased from 85 as of January , 200� to 1�7 as of January 1, 2007. At that point, average IPT lifespan was 4.� years, and the average age of IPT leaders was 4�.4.

Technology TransferOne priority for the Institute’s strategy has been technology transfer. INRIA continues to invest in human and financial resources to improve quality and efficiency, parti-cularly by increasing the number of CDRI (Development and Industrial Relations) posi-tions, strengthening the DirDRI, and setting up EDT (Experimentation and development tech-nical units). This organization combines the work of the CDRIs, which work closely with the teams and partners in each center, with greater coordination and support responsibilities for the DirDRI: leading strategic partnerships, a specialized department for managing intellec-tual property, implementation and promotion of licenses for open source software. The Institute concentrated on strong partnerships with major market leaders, both French and foreign. These mid- to long-term partnerships have been an essential tool in cooperation with large industrial companies seeking to share their research and development costs. Such major partners have included FT R&D, EDF, Alcatel Lucent and Thalès.Professionalizing the software development

activity and improving the quality of these developments have also become crucial priorities to ensure success and continue encouraging research scientists to optimize the most suitable technology transfer mode from among the broad range of commercial software licenses and open source software options. Each year, �0 to 70 software packages are now registered by the Institute’s teams. Technical units have been created and conso-lidated to support, professionalize and sustain technology development efforts of IPTs. Technology start-ups are an excellent way of transferring technology, as demonstrated by the creation of 2� start-ups between 200� and 200�.

Training and Knowledge TransferINRIA has come to see its contribution to training through research for young PhD students in computer science and applied mathematics as one of its essential tasks, carried out in close cooperation with its partner doctoral engineering schools. It continues to be very active in doctoral training, focusing on the quality of theses prepared within its research project-teams and, more generally, the quality of training received by PhD students and their preparation for entering professional life after their thesis. The number of PhD students in project-teams rose from 7�0 as of January 1, 200� to 1,070 as of January 1, 2007. The number of theses defended rose from 150 in 200� to 291 in 200�. To facilitate this increase in the number of PhD students while maintaining very high quality in terms of recruitment, INRIA set up a state-funded PhD program to encourage mobility and host foreign PhD students. In 200�, 25 subsidized (CORDI-S) INRIA doctoral research contracts were made available, generating over 1,500 applications. The PhD students recruited were all from other doctoral schools, and 85% of them had a foreign nationality. In 2007, 40 new CORDI-S were made available. In addition to its involvement in doctoral training, INRIA also extended its program for hosting subsidized post-doctoral researchers: the number rose from �7 in 200� to 80 in 2007. More and more young engineers are acquiring additional technological training through research at INRIA, usually followed by recruitment into the industry.


The Control Action Table, a 6 DoF interface for virtual reality — IPARLA.

European Partnerships The creation of the European partnerships department demonstrated that building and developing the European Research Area is a high priority in the Institute’s policy. Following the fifth FP, where the Institute participated in 110 projects, the sixth FP was a challenge for INRIA and confirmed its place as European leader for ICST research, particularly in the field of software develo-pment. As part of this program, INRIA has participated in 119 European projects, inclu-ding 21 excellence networks, �2 integrated projects and 45 research projects, in liaison with industrial partners, and has been respon-sible for the scientific coordination of 15 of these projects.With the Institute’s support, the ERCIM consortium (European Research Consortium on Informatics and Mathematics, which now brings together 18 national bodies) has gradually become more representative of the scientific and technological community in the field of ICST. Its international visibility was consolidated when INRIA entrusted it with the responsibility of European host of W�C. The Institute has continued its efforts to develop relationships with major European industrial players: examples include taking part in the Eurêka program, particularly as part of the ITEA program, and setting up the AIR&D laboratory jointly with Philips, Thomson and the Fraunhofer Institute.In all major countries, the importance of regions in international cooperation has increased, and INRIA research centers have become involved in the international relations of the regions in which they are located. Partnership agreements have been signed with institutions located in Sarrebrücken and Kaiserslautern (several universities, the Max Planck Institute and DFKI), and these are promising examples of this policy.

International RelationsIn a context where ICST is prioritized in national research policies everywhere, INRIA has continued to expand its international cooperation, targeting most of its efforts at a few major partnerships in certain geogra-phical areas.Asia has been the top geographical prio-rity outside Europe. The Franco-Chinese

laboratory LIAMA, in Beijing, which played an important part in expanding cooperation with China on ICST, has been bolstered by the possibility of INRIA granting expatriate status to some of its research scientists: 4 research directors are in charge of joint teams along with the Institute for Automatic Control at the Chinese Science Academy and the University of Tsinghua respectively. The LIAMA is part of an ambitious open-source software deve-lopment project by the Scilab consortium set up by INRIA. The Institute has also continued to develop cooperation programs with Hong Kong, Singapore, Taiwan, Korea and Japan, notably with major industrial companies such as Hitachi. A student exchange program has also been developed with India. The number of Asian trainees in the INRIA International Internships program rose from 2� in 2004 to 54 in 2007.INRIA’s relationships with the United States and Canada have of course been very dynamic, with active cooperation involving over one hundred universities and companies. The United States’ undisputed leadership in the field of ICST has made it vitally impor-tant to hold ongoing dialogue with the NSF and also to establish relations with the NIH in the fields of modeling living systems and medical technology.Partnerships with southern countries have also been strengthened. In particular, INRIA has maintained its support for Africa with the biannual CARI symposium and the scien-tific interest group SARIMA.The partner team program, in which an INRIA research project is linked to a team of researchers in a foreign institution, has continued its successful expansion. The number of partner teams rose from 2� in 2004 to 54 in 2007.Finally, the Institute’s scientific staff has conti-nued to broaden its international horizons, with the proportion of foreign research scien-tists, post-doctoral researchers and engineers on INRIA’s staff exceeding 15% in 200�.

Research Support and Management StructuresIn addition to the criteria of excellence and relevancy for research and technology transfer, the Institute’s work is also assessed in terms of how efficiently it is run.


History

1�Strategic Plan 2008-2012

ICST is prioritized in national research policies everywhere.

Increased quality and efficiency of research support and assistance was a priority during this period:• an improved information system, geared

to the planned changes for budgetary and accounting management for EPSTs, was developed, deployed and gradually rolled to all different levels of work within the Institute;

• the policy of decentralization was continued, and a “quality procedure” was developed to manage stakeholder accountability; some administrative and financial responsibilities were decentralized by making research unit directors responsible for giving orders; a new computerized library management system was acquired and deployed in all research centers, providing access to a shared catalogue for the various document collections;

• a Hal-INRIA open archive server was imple-mented, providing research scientists with direct access to scientific literature;

• enhanced management and management control methods and tools were implemented under the modernization and simplification protocol signed with the public accounts office; a “partnership control” was developed with the accounting department; a mana-gement culture was encouraged within the Institute through a sustained training effort; flexibility and anticipation were improved, in particular for purchasing.

The Institute defined and implemented an ambitious policy on IT and communications equipment to the best international stan-dards, with very high performance networks, computing and visualization resources and grids allowing for far-reaching experiments to be run and technological developments implemented. Developing a dynamic human resources policy has been a main prio-rity. Heavy involvement by INRIA staff has helped the Institute’s extensive recruitment campaigns to achieve success, and scores of INRIA staff who had been working under precarious employment conditions for several years gained more stable footing thanks to the publication of new regulations and the high level of commitment by the Institute’s direc-tors. INRIA designed and drafted a manager’s guide for use in supervision and management training. Ongoing staff training efforts were

significantly increased. Internal and external staff mobility was particularly encouraged. Widespread open mobility campaigns for all government positions provided for many support jobs to be opened for temporary assignments. Lastly, a system was imple-mented to maintain an ongoing relationship with former INRIA personnel.


INRIA Today: Burgeoning

Scientific Fields

As in other major scientific fields, ICST research includes producing and organi-zing knowledge as well as extracting and perfecting general and in-depth ideas that are then analyzed, developed and applied. These ideas aim to solve many new and sometimes unexpected problems, whose emergence often results from extremely rapid technological progress, particularly the exponential increase in the power of micro-processors, the communications capacity of fiber optics, memory density and magnetic disk capacity, as well as the considerable impact of widespread web implementa-tion. The miniaturization of sensors and the increasing quantities of available data have also led to new scientific develop-ments creating new algorithms which aim to analyze these data and regulate, control and simulate increasingly complex systems. Lastly, interaction with other sciences is a vital component of computer science, automatic control and applied mathematics. This works both ways: the other sciences reveal new problems for information proces-sing and modeling and, conversely, the existence of new design and simulation tools can change the issues at stake and even certain paradigms in these sciences, sometimes profoundly. In this sector more than many others, the positive feedback loop linking basic research and applica-tion is at its best. Research, even in its purest form, can be used to develop new products at an exceptionally rapid rate, as the horizons opened up by new technologies call research areas into question, often at the most basic level. In every field, behind the brilliant success of technology and the developments facilitating the creation of innovative new companies, there is pure research - leading to new theories, new models and new software tools and giving various scientific fields a new lease on life. At this point it is important to emphasize the relationship with other sciences, which play a major role in INRIA’s scientific policy. First of all, it is a great advantage for one single institute to be able to gather together specialists from many disciplines − computer science, automatic control, signal processing and scientific computation − which are often

separated into different organizations, both in France and abroad. INRIA’s potential for scientific and technological contribution would be much more restricted and narrow if it were simply a computer science research institute, since the interactions between computer science and applied mathematics are constantly growing; furthermore, they are essential in order to meet new challenges in the ICST sector and its interactions with other fields. Consequently, INRIA’s direc-tors are constantly seeking to ensure that research is conducted and assessed within the Institute in a way that breaks down the borders between disciplines and overcomes the separation inherent to organizational structures. In this context, interactions between mathematics, physics, chemistry and mechanics were explored right from the very start of the IRIA and have recently been taken in new directions, as demons-trated by the contributions made in recent years in algorithmic and stochastic geometry and computational chemistry. During the last decade, interaction between INRIA and the environmental sciences has been increasing in many directions as well, parti-cularly with the life sciences: some examples include bioinformatics, molecular biology, neurobiology, biomechanics, modeling of organs and physiological functions, plant growth modeling and simulation, medical robotics and renewable resource modeling. INRIA believes that the interaction between ICST, the life sciences and applications for medical technologies and the environment will play a crucial and far-reaching role in science over the next few decades, just as the profound interaction and mutual enri-chment of mathematics and physics have played a major role in the scientific progress of recent centuries. Lastly, cross-functional issues relating to security, developing an information-based society, education and sustainable development will all benefit from the progress of ICST research. Before concluding this brief overview, one last key point should be mentioned. INRIA believes that its research is subject to a parti-cular type of “tension”: ferocious competition over research applications combined with the rapid progress of technology make ICST a


History


Visualization of geological surfaces in a virtual reality interface — ALICE.

field of research where time is of the essence. While it finds this tension very stimulating and productive, INRIA also believes that despite the constantly increasing demand for work on short-term issues, the Institute must continue to focus its energy on pure

research, which is the key to its ability to deepen its understanding of its scientific fields and anticipate developments and technological innovations in these fields over the medium to long term.

1� Strategic Plan 2008-2012

The Cognitive systems field focuses on man-machine interaction. Cognitive psychology and ergonomics help make computer systems more user-friendly. Using and manipulating multimedia databases involves data searches, interoperability between databases and natural language interfaces, as well as indexing, knowledge representation, statistical modeling, learning and reasoning. Many new applications are placing more and more emphasis on images. Image analysis covers such varied fields as satellite images, new medical imaging methods, indexing of video documents and managing robotic systems. Computer-generated images enable enhanced and virtual reality, and when used with simulation, become man-machine interaction resources that are particularly suited to fields such as design, surgery and scientific calculation. Network development brings with it a new set of considerations for the transmission and encoding of multimedia documents.

Cognitive systems

Cog-A 7 IPT Statistical modeling and learning

Cog-B 8 IPT Images and video: perception, indexing and communication

Cog-C 9 IPT Multimedia data: interpretation and man-machine interaction

Cog-D 7 IPT Computer-generated images and virtual reality

2

Major Fields of Research at INRIA

The Communicating systems field focuses on issues often raised in designing and implemen-ting the computer tools required for current and future information systems. These consist of computer systems where multiple processing units are spread out across communication networks, with particularly high standards of reliability, availability and performance, such as real time operation. This is primarily a question of architecture and systems: tools for designing specialized processors and compiling and optimizing source code, especially for embedded systems. Distribution and mobility of computational processing, real time operation and inte-roperability call for synchronous programming, reactive programming and communicating processes. Meanwhile, network dimensioning and metrology require probabilistic modeling, simulation and graph theory. The design and study of protocols suitable for broadband and for the characteristics of the new ubiquitous networks (wireless, mobile, heterogeneous, etc.) is a very active field.

Communicating systems

Com-A 12 IPTDistributed systems and shared architectures

Com-B 10 IPT Networks and telecommunications

Com-C 10 IPTEmbedded systems and mobility

Com-D 3 IPT Architecture and compilation

1

INRIA’s 150 research project-teams are involved in five major research topics, and 16 more specific sub-topics. This distribution helps to identify INRIA’s strengths according to these five major topics and, above all, organizes the Institute’s assess-ment process. Teams from any center working on the same sub-topic (on average a dozen teams) are simultaneously assessed by one panel of international experts (for more details on the assessment process, see paragraph 4.3.6). A brief description of each of these five major issues and a list of the sixteen sub-topics, with the corresponding number of INRIA project-teams (IPT in December 2007) is given below.


History


The field of Symbolic systems focuses on designing and experimenting new programming tools in order to master the increasing complexity of software applications, improve their reliability and guarantee secure implementations. This requires high-level languages that feature generic concepts such as objects and constraints, and composition principles such as component programming and aspect programming. Research in this field also exami-nes compilation and automatic and interactive tools for testing programs and program properties, including checking computer arithmetic. New applications call upon more complex algorithms for cryptography, algorithmic geometry, robotics and bioinformatics. Designing and analyzing these algorithms use algebraic and geometric structures as well as new mathematical methods and symbolic computing. Research into content and language organization is also being carried out.

Symbolic systems

Sym-A 12 IPTsSoftware security and reliability

Sym-B 10 IPTs Algebraic and geometric structures, algorithms

Sym-C 10 IPTs Content and language organization

3

Bio-A 12 IPTs Modeling and simulation for biology and medicine

The field of Biological systems focuses on modeling and simulation for biology and medi-cine: analysis and simulation of medical images and biological phenomena, understanding biological vision, bioinformatics, medical robotics and artificial movement. Current subjects of study include modeling plant growth, as well as modeling and controlling renewable resources.

Biological systems5

Numerical systems

Num-A 7 IPTs Automatic control and complex systems

Num-B 11 IPTs Grid and high-performance computing

Num-C 8 IPTs Deterministic and stochastic models: identification and optimization

Num-D 14 IPTsSimulation and numerical analysis for physical models

The field of Numerical systems looks into new methods for modeling, simulation, optimi-zation, large-scale problem solving in engineering, economics, medicine, biology and the environment, and more generally stochastic or large-scale inverse problems. The theory of complex systems and their control, signal processing and data analysis applies here to robotics, industrial systems management, road and air transport, non-destructive control and telecommunications, as well as to biology and environmental issues. Simulating complex phenomena in the engineering sciences (fluid and structural mechanics, semi-conductors and electrical engineering, meteorology, new materials), financial models and models of living organisms involves a search for mathematical models, often requiring interaction between different scales and different physical phenomena, and the development of accurate and high-performance computational methods for large-scale computational simulations. In addition to grid computing, large-scale computational applications require parallel or distributed programming, program transformation and distributed application management.

4


INRIA Research Centers

The eight INRIA research centers in existence as of January 1, 2008 are briefly described in the boxes on the following three pages. Their scientific orientation in terms of this strategic plan is described in chapter 4 (cf. 4.2).

INRIA

Bor

deau

x

SudO

uest

INRIA Bordeaux – Sud Ouest Research Center, along with Lille and Saclay, is one of the three centers that were incubated in the INRIA Futurs research unit between January 2002 and December 2007. It was established as a center in its own right on January 1, 2008.

Its 13 research teams (7 IPTs) were formed through close partnerships with the Bordeaux and Pau universities and with the CNRS, or more specifically with their laboratories: the LABRI, IMB, LMA and MIGP. These dynamic partnerships, in addition to staff transferred from other INRIA sites and a recruitment policy for research scientists and top-level research support staff, meant that the research center had a workforce of 273 by the beginning of 2008, 111 of whom are paid by INRIA, including 27 research scientists and 21 government-employed support staff.


History


INRIA

Bor

deau

x

SudO

uest

INRIA

Gre

noble

Rhône

-Alpes

INRIA Grenoble - Rhône-Alpes Research Center was founded in 1992; it has a workforce of 500, 260 of whom are paid by INRIA, including 75 research scientists and 66 support staff.The center’s main site is at Montbonnot, near Grenoble. Almost one quarter of the workforce is in Lyon, at the ENS sites in

Gerland and on the Doua university campus. At the end of 2007, the center, which has eight research support departments, had 26 research teams (23 IPTs). Most of these are shared with the CNRS and/or local universities; they were formed with the help of close partnerships with the universities of Grenoble and Lyon (Joseph Fourier University, National Polytechnic Institute of Grenoble, Claude Bernard University), the Lyon École Normale Supérieure and the Lyon INSA, in addition to the CNRS, and more specifically their laboratories including the LIG, LJK, LIP and CITI.In the area of technology transfer, the center has focused on start-ups, creating 14 companies since 1999, 3 of which were incubated, and on partnerships with major local players such as ST Microelectronics, France Telecom and Xerox.


INRIA

Lille

Nor

dEu

rope

INRIA Lille - Nord Europe Research Center, along with Bordeaux and Saclay, is one of the three centers that were “incu-bated” in the INRIA Futurs research unit between January 2002 and December 2007. It was established as a center in its own right on January 1, 2008. It now has a workforce of 200, 80 of whom are paid by INRIA, including 18 research scien-

tists and 15 support staff. The Center’s 10 research teams were formed with the help of partnerships with Lille University of science and technology (Lille 1), Charles de Gaulle University (Lille 3), Lille Ecole Centrale and the CRNS. There are seven joint IPTs with the LIFL, two with the LAGIS and one with the Paul Painlevé laboratory (UMR 8524 CNRS and USTL mathematics laboratory). In spring 2007, the center moved into a 4,000-m2 building located in the Haute Borne science park, on the edge of the USTL and Lille École Centrale campus, which was purchased with the help of local government and European funding.


History


INRIA

Nan

cy

Gra

ndE

st

INRIA Nancy – Grand Est Research Center was founded in 1986; it has a workforce of 480, 210 of whom are paid by INRIA, including 63 research scientists and 65 support staff.Its 22 research teams (21 IPTs) were formed with the help of partnerships with Henri Poincaré University in Nancy, the

universities of Metz, Nancy 2 and Strasbourg, the INP in Nancy and the CNRS, and specifically with their laboratories, LORIA (Lorraine laboratory for computer science and application research) and IECN (Institut Elie Cartan). INRIA is also present at the Metz, Besançon and Strasbourg sites through dual-location project teams in cooperation with Nancy. INRIA Nancy – Grand Est Research Center is developing international projects and special cross-border cooperation with the Saar region. In the area of technology transfer, it has set up 9 companies since 2000, and circulates forty or so software packages.


INRIA

Par

is

Rocqu

enco

urt

Founded in 1967 at the same time as the Institute, INRIA Paris-Rocquencourt now has a workforce of 600, 370 of whom are paid by INRIA, including 128 research scientists and 130 support staff.It has 9 departments and 35 research teams (31 IPTs), 17 of which are joint teams with Pierre et Marie Curie University

(Paris 6), Denis Diderot University (Paris 7), Marne-la-Vallée University and Versailles - Saint-Quentin University, the École Nationale des Ponts et Chaussées, the Paris École Normale Supérieure, the National Higher School of Advanced Techniques and the CNRS.Its highly effective teams have enabled the Center to set up 25 companies and circulate 50 high-quality software packages, half of which are open source.


History


INRIA

Ren

nes

Bre

tagn

eAtla

ntique

INRIA Rennes - Bretagne Atlantique research center was founded in 1979 when IRIA became INRIA. In Rennes and Lannion, it is a partner of the CNRS, the University of Rennes 1 and the Rennes INSA, together with the IRISA, UMR 6074 and Cachan ENS (Brittany branch). There are two joint project-teams in Nantes cooperating with LINA (part of the

University of Nantes, the Nantes École des Mines and the CNRS). The research center has a workforce of 580, including 67 INRIA research scientists, 82 research scientist professors, 15 CRNS research scientists, 80 INRIA support staff, 21 technical and administrative support staff from other establishments, approximately 180 PhD students and 25 post-doctoral researchers. There are 7 research support departments and 26 joint project-teams cooperating with one or several of the partners mentioned above. A large part of the research work is conducted in the framework of bilateral partnerships (international academic partners, applications partners, major industrial groups, SMEs, state bodies) or multilateral programs (national research agency, competitiveness clusters, European programs with participation in over 40 projects in the 6th framework program). More specifically, the center is very involved in the Images & Networks competitiveness cluster. The creation of innovating compa-nies and the application of software and patents complement the technology transfer field.


INRIA

Sac

lay

Île-d

e-Fr

ance

The Saclay - Île-de-France Research Center, along with Lille and Bordeaux, is one of the three centers incubated in the INRIA Futurs research unit between January 2002 and December 2007. It was established as a center in its own right on January 1, 2008. INRIA Saclay - Île-de-France Research Center has a workforce of 350, 180 of whom are paid by

INRIA, including 50 research scientists and 38 support staff.Its 21 research teams (15 IPTs) were formed through close partnerships with the University of Paris-Sud, the École Polytechnique, the Cachan École Normale Supérieure, the CNRS, and more specifically with their laboratories: the LRI, the LIX, the LSV, the CMAP and the University of Paris-Sud’s mathematics department.


History


INRIA

Sop

hia

Antipolis

Méd

iterran

ée

INRIA Sophia Antipolis - Mediterranée Research Center was founded in 1983; it has a workforce of 460, 340 of whom are paid by INRIA, including 119 research scientists and 80 support staff.Half of its 30 research teams (28 IPTs) were formed through close partnerships with the Universities of Nice-Sophia Antipolis

and Montpellier, with CNRS, the INRA and the CIRAD, and in particular with the I3S, JAD and LIRMM laboratories.The center works in close collaboration with companies located in its geographical area and elsewhere, and its teams are working on over 40 European-level projects. It is involved with the work of eight competitiveness clusters and is a foun-ding member of the world SCS cluster (Secure Communications Solutions). It plays a key role in the Sophia Antipolis tech-nology cluster by actively participating in associations such as Telecom Valley and through the Center’s 15 spin-offs. It is also involved in development for the Montpellier cluster, particularly through its contributions to the Montpellier Agricultural Research and Sustainable Development foundation. Lastly, the center is home to the ERCIM office and the W3C European development team.

Inthischapter:

ICST Research: Context and Key Issues

2.1 SocietalIssues page28

2.2 ScientificandTechnologicalChallenges page31

2.3 TheInternationalandNationalFramework

forICSTResearch page33

2.3.1 InternationalContext page33

2.3.2 EuropeanContext page33

2.3.3 FrenchContext page34

Context


Societal Issues2.1 Information science and technology are present

in virtually all business sectors. They play an essential role in accelerating scientific and technological progress and increasing produc-tivity and growth. The new infrastructures and resources for communication, interaction and production have vastly altered the economy, in the broad sense of all exchanges between people and within an entire society.ICST is radically changing the methods and resources used by scientists and engineers to observe, draw conclusions from vast quanti-ties of data, represent and abstract, model, visualize, design and make decisions. This technology is at the heart of computational sciences and computational engineering. INRIA has made its strategic choices so as to meet the challenges posed by society and by the economic issues that ICST helps to solve.The greatest challenge in social terms is to improve living conditions for all of mankind, narrowing the gap between North and South

and protecting the earth’s environment. This challenge takes the form of seeking sustainable development, improving health, addressing the aging that results, and providing universal access to knowledge. In addressing environmental issues, combi-ning modeling and simulation with the poten-tial for observation and detection enables the complex, natural phenomena at play to be examined with ever-greater precision. These methods can provide tools for forecasting, forming strategies, prevention and adapta-tion, scenario analysis and risk assessment of a given environmental policy or of a lack of action. They supply essential tools to examine vital risks linked to the build-up of greenhouse gases and major climatic and oceanic changes. The possibilities for demonstrative display of forecasts can be used to influence public opinion in favor of prevention, a long-term approach that requires resources and a strong commitment by politicians and society. In the field of sustainable development, long-term solutions must be found for the needs of mankind – some 9.5 billion people by the middle of the century. Meeting food requirements will demand that soil erosion, impoverishment and pollution through overexploitation and overuse of fertilizers and pesticides be brought under control. Agricultural production requirements can be met without impeding sustainable deve-lopment if the needs of both plants and their environment are taken into account. Modeling and computing techniques can make a signi-ficant contribution to solving these and other related problems, such as the issue of fishing resources.These techniques, in addition to design, opti-mization and automatic control, may also help to meet energy requirements. Support for designing HEQ buildings and intelligent management using different energy sources, in particular renewable sources, could be provided online by means of control/command systems implemented for a house, building or town. Active control can be found everywhere where energy needs to be saved, particularly in various modes of transport, where electric actuators are being increasingly used. Finally, ICST may also help in managing new energy sources: biofuels, solar, geothermal, wind, and the future ITER project generators.Health is an area where ICST has made a

2.1 Societal Issues

Context


ICST is radically changing the methods and resources used by scientists and engineers to observe, draw conclusions from vast quantities of data, represent and abstract, model, visualize, design and make decisions.

major impact over the past few decades and which offers significant possibilities for scientific and technological progress. Areas of interest include major viral diseases, cancer and neuro-degenerative disorders. INRIA is very involved in this field. Other noteworthy activities include: integrating various medical imaging and measurement methods with multi-physical modeling in order to obtain high-definition, personalized representations of organs; epidemiology modeling; modeling the effects of drugs; bioinformatics (which has led to spectacular progress in genomics and post-genomics); the design and control of organs and palliative care for sensory or motor impairment; and robotic-assisted surgery. Over and above these state-of-the-art technologies, patients remain the focus of any healthcare mechanism, such as setting up appropriate information systems and developing at-home care using remote monitoring, remote medical care and even, in some circumstances, remote surgery.Demographic changes, specifically population aging and urban concentration, open up other areas of intervention, for example indepen-dence for the elderly, safety and security, urban organization and transportation issues.The safety and protection of people and organizations is becoming a major issue for developed societies; information technology is once again at the forefront, both in terms of risk factors and protection tools. Intelligent monitoring, biometrics and tracking techni-ques aim to improve security; the necessary precautions must be taken so that they do not hamper personal freedom; this is yet another example of the essential link between ICST and society. Encryption is one technique for protecting information exchanges, but other aspects of security and confidentiality are just as important: detecting fraud and intrusions, combating economic espionage and cyber crime in networks and protecting privacy.In the field of private transportation, com-puter-assisted driving and safety functions are becoming more complex and more widespread. There is room for improvement in overall archi-tectural design, optimization and vehicle and transit system reliability. More generally, ICST can contribute through real-time or delayed optimization: multimodal journeys for private individuals, logistics, road/rail freight, modular

public transit and new modes of travel. The techniques of geo-location, personal spatial information and ambient intelligence open up new methods of urban organization and expand freedom of movement, particularly for disabled people.Education, learning and training are essential to a knowledge society. Communication, visua-lization, virtual reality and interactive tools can meet these needs, in particular by providing access directly to the semantic content of information and using natural languages and modes of interaction (speech, vision, body movement).One important characteristic of information and communication technology is its high potential for boosting economic and industrial growth. It has already had a significant impact. Estimates show that almost half of world economic growth now stems from ICST. The production of goods has become considerably more effective and flexible, leading to highly differentiated supply, and customized products with high added value. ICST has become an essential factor in industrial innovation through the new engineering and production possibilities it offers as well as its ability to offer unprecedented features by integrating – into a wide range of devices – sensors, actuators, communication and data processing circuits. ICST’s role in all products, particularly products intended for the general public, is expanding rapidly. In services, the growth of ICST is even more rapid. Electronic commerce between companies, and increasingly between indivi-duals, is experiencing spectacular growth. The same is true of electronic exchange services, which are based on the technological capabili-ties of the Internet, ubiquitous access and the manipulation of semantic content. Networking among businesses and people has changed the way work is organized, for example by allowing greater versatility, autonomy and delegation of responsibility. These changes are continuing with the develo-pment of collaborative work technologies. The notion of collective intelligence is now taking on practical meaning in all sectors, as internet users become involved in everything from epidemiology studies to expert services and technical problem solving, from engineering, designing, testing new products and marketing to large-scale economic, political and social

�0 Strategic Plan 2008-2012

studies. The companies behind these services rely on increasingly vast and ever-changing virtual communities; they are building new types of working relationships. The growing possibilities for sharing and capitalizing on information, models and open-source software to process this information are creating subs-tantial economic value. The information society has been respon-sible for radical changes in businesses, local government, municipalities, public services and the organization of society. Digital tech-nology is increasingly becoming a necessary part of our daily, political and social life, for example in all electronic administration tools and political debate. The computerization of administration and all forms of exchange will continue, creating related needs for security and protecting the rights of individuals and companies. No doubt much remains to be done in this area before our information society is truly at the service of mankind, particularly as new users continue to arrive. ICST itself has to provide the means for reaching this goal. Access for all to information and knowledge requires considerable effort to make equip-ment widely available (networks, computers and software) and easy for non-specialists to program, adapt and use naturally, all of which requires specific research. More generally, the considerable progress made in all ICST fields (e.g., miniaturization, intelligent information searching, image proces-sing) will bring into reach scenarios which not so long ago were seen as pure science fiction, or even threats (e.g., an Internet of things, memory prostheses, inserting multiple RFID chips into the human body, tracking objects and individuals). It goes without saying that these applications will have a considerable impact on how society develops and raise many fundamental legal, ethical and techno-logical issues. Large-scale adoption of tech-nologies such as the Internet and new means of creating and disseminating knowledge and digital property already raise many legal issues: the protection of privacy, liability, intellectual property and non-discrimination. Issues of formal proof, certification, software liability and insurance, and of course problems with social acceptance and ergonomics have also arisen. Furthermore, ethical issues are becoming increasingly important, for example with respect

to micro- and nanotechnology. All of this is at the heart of a social debate that will be more productive if scientific knowledge and culture have been disseminated. Such issues also demand a closer relationship between ICST and the human and social sciences, in the areas mentioned and in others as well, particularly sociology, ergonomics and economics.The Institute needs this type of interdisciplinary cooperation to understand and consolidate its position within our information society. It is also very productive in terms of research, opening up scientific issues to be examined afresh and raising new areas for investigation. INRIA will be redoubling its efforts in this domain and taking steps to set up interdisciplinary projects esta-blishing long-term relationships with partners in the human and social sciences.All of these challenges demonstrate that INRIA is working in an area essential to France’s economic and industrial development. The Institute is deeply committed to these social and economic issues and has a long tradi-tion of industrial partnerships and spin-offs. It intends to expand its work in technology development and technology transfer, thus enlarging the economic and social impact of its technology.

2.1 Societal Issues

Context

�1Strategic Plan 2008-2012

Scientific and Technological

Challenges

2.2 As an internationally renowned research insti-tute, INRIA must maintain a central role in pure research in applied mathematics, computer science and automatic control if it is to further knowledge, prepare for the technological innovations of the future and meet the social challenges discussed above. The Institute must also face the major scientific challenges that will confront ICST in the coming years, in particular those likely to occur within the scope of this strategic plan.Analyzing today’s digital environment reveals a drastic change in scale in terms of the size and complexity of systems of reference. In the area of networks, the Internet now interconnects 2 billion devices. This figure will continue to skyrocket, particularly given the projects for very low cost personal computers. The trend is moving toward an Internet of things that would connect a substantial number of arti-facts. The advent of nanotechnology heralds the possibility of intelligent dust: tiny devices with sensors, computing and communications capabilities.The arrival of new network architectures raises questions of how to achieve very large-scale and highly flexible distribution and communi-cation, heterogeneity, interoperability, forward compatibility, suitability to the environment and intelligent interaction at an operational level with the user, as well as issues of auto-nomy in terms of power supply, operations and decision making. A technology’s invisi-bility in day-to-day use is a good measure of its maturity. Clearly, a number of scien-tific challenges must be overcome before a very high degree of technological maturity is achieved in the field of ICST. Interaction of humans with machines must be transpa-rent and use all our natural faculties in both directions of communication: vision, natural spoken language, body movements and touch. Furthermore, intelligent interaction between machines not only demands interoperability but also requires each network component to be capable of exporting an intelligible and relatively full model of the services it can provide, how it works and what its constraints are; each component must also be able to correctly interpret the various components of the other models with which it may be interfaced. This exchange must be possible with an open set of models, and at different

levels of granularity between components of a sub-system, between sub-systems, and so on. Furthermore, the functional autonomy for a machine requires the sensory capacity to perceive and interpret the environment, as well as the ability to supervise, diagnose, predict, plan and even learn.The scale of the data volume and complexity to be processed has also changed radically. In 200�, an estimated 1�0 billion gigabytes of data were created; this figure will be 1000 billion gigabytes by 2010, with a large portion of the data available on the network. Beyond considerations of quantity, new search engines will have to deal with increasingly varied, rich and complex semantic content and provide an effective, intelligent search for information relevant to the user. The traditional algorithms used in these areas will have to be revised to cope with the changed expectations for scale, quality and intelligence of processing, and also to provide faster reaction time and enhanced interactivity and suitability for users – aspects which, as yet, are often imperfect.It is also important to raise the issue of compu-ters of the future that will be required to take over from our present-day machines, as their performance is beginning to reach its limits. Even if we believe that technological impro-vements such as multi-core architectures can produce further progress, the computers of the future will likely use a radically new design, perhaps based on an optical, quantum or biological mechanism. Such progress will revolutionize the way we see the future of ICST in many fields, with cryptography and problem-solving among the most affected.Furthermore, ICST is at the heart of most of the major interdisciplinary challenges of our age, in the material, life, earth and universe sciences, as well as the human and social sciences. For the computational sciences, the challenges will include developing representations and complex, heterogeneous models integrated into sensors and data and implementing them in efficient computing, as well as developing processes for organizational and information searches, synthesis and optimization, verifi-cation and proof, forecasting, simulation and precise visualization. The interdisciplinary issues relating to the environment, ecology and sustainable development mentioned above open up vast areas for research in these


Map of the anatomical variety of the brain (seen from the left side) — ASCLEPIOS.

domains. Vital scientific and technological challenges must be met in order to understand life and observe, analyze and model biological functions at all levels - molecules, cells, organs and complete organisms. The possibilities for ICST range from nano-biotechnology, lab-on-a-chip technology, bioinformatics and multi-modal imaging to modeling a highly complex organ such as the brain.Our brain is the organ we use to explore and communicate with our environment, to form the mental pictures necessary to plan and act; understanding it is one of the great adventures of science. At stake are not only the answers to long-standing questions about our uniqueness as a species and awareness of the world, but also an urgent, legitimate and multi-faceted social demand in the form of public health concerns such as mental illness and dege-nerative disorders, addictions, physical and sensory disabilities and dementia. Medical applications involve processing and analyzing imaging data in the broad sense in order to develop models, algorithms and simulations to help treat diseases of the central nervous system. In addition to these uses, computa-tional neuroscience recognizes the central nervous system as one of the most sophis-

ticated information processing systems in existence, whose workings are far from being understood. How information is represented (neuronal codes), stored (types of memory, redundancy), updated (learning, plasticity) and processed there are fundamental ques-tions. This major scientific challenge is one in which INRIA, among others, has a contri-bution to make. Beyond merely acquiring knowledge, which is certainly an important goal, this research opens the door to innu-merable potential applications, including the development of new types of machines for processing information ‘neural computers), new brain-machine interfaces, new hearing and vision prostheses and new, more effective therapies for people with neuro-degenerative disorders.The problems mentioned above fall into various scientific fields within information science and technology. Sections �.1 and �.2 describe the seven areas that INRIA has chosen to focus on and prioritize. The Institute will still remain open to other areas of research and encourage initiatives such as those presented in section �.4 on emer-ging technologies or, on the European level, participating in the ERC.

2.2 Scientific and Technological Challenges

Context

��Strategic Plan 2008-2012

The International and National

Framework for ICST Research

2.3 2.3.1 InternationalContext

ICST is perceived as a leading factor of growth and development, making it an R&D priority worldwide. To paint a broad picture:• the total amount of R&D investment for ICST in

the United States in 200� was 71 billion dollars (G$) in purchasing power parity - twice that of Japan and the 25-nation European Union;

• in 2005, China moved into second place worldwide for industrial R&D in ICST, inves-ting �8.7G$. This amount is slightly higher than that of Japan (�4.1G$), which in turn is higher than that of the 25-nation European Union (22.1G$);

• after the four giants - the United States, China, Japan, and Europe - other players rank as follows (with the main European countries classified separately from the community): Korea, India, Brazil, Germany, France, United Kingdom, Taiwan, Canada, Russia, Sweden, Finland, Israel, Singapore.

In the United States, military programs largely influence ICST funding, mainly in supporting industry. ICST funding in Japan and the rest of Asia is characterized by heavy investment from the private sector. In Europe and particularly in France, public budgets and public research play a major role, with a relatively low level of private investment.The key issues in the United States, based on the NITRD program’s coordination, are high-perfor-mance computing, networks, man-machine interactions and the use of massive data sets, software engineering, software and systems security and reliability and socio-economic aspects (training, education, social use). The telecommunications industry has been the target of important initiatives by DARPA and the NSF. In addition, the American Competitiveness Initiative lists high-performance computing, advanced networks and cyber infrastructure, complex modeling and simulation for engi-neering and cyber security among its major national priorities.In China, ICST research is managed as part of a program under the Ministry of Science and Technology (the MOST high-technology development program). It focuses essentially on intelligent perception and advanced computing technologies, intelligent networks and commu-nication technologies, virtual reality technologies and cyber security.

In Japan, the major trends for government action on ICST prioritize ubiquitous IT, with the u-Japan plan (FTTH fiber optic connections, wireless networks, IPv�, the internet of things, RFID), super calculators (development of a super calculator capable of up to ten petaflops, destined to be the most powerful in the world by 2011) and robotics. The Japanese Ministry of Industry sees robotics as an industry of the future, in particular domestic and service robotics, with a market estimated to be worth 50G$ by 2025.

2.3.2 EuropeanContext

In 2000, the European Commission launched the “European research area” concept with the aim of coordinating research and innovation, for both member states individually and the Union as a whole. Previously, research at the European level was confronted with many diffi-culties: fragmented efforts, isolated national research systems and disparate regulations and administrative systems, in addition to low investment in research, well below the Lisbon targets.For the period between 2007 and 201�, the Commission will invest in research in keeping with the 7th FP, which is organized into four major programs: Cooperation, Ideas, People and Capabilities. The relatively tradi-tional Cooperation program allows for indus-trial players and research organizations to develop cooperative R&D operations. The Ideas program, which is far more ambitious in terms of pure research, will enable research scientists to invest themselves fully in prelimi-nary research work with significant financial support over a five-year period. The European Research Council has been set up to manage the scientific aspects of this program. The People program relates to the mobility of research staff within the European Union and to the creation of a “European research scien-tist” status, which is deemed necessary in forming European teams and laboratories. The final program, Capacities, is largely concerned with major research infrastructures. The 7th FP has a budget of 50.5G€ for 2007-201�, 1G€ of which is earmarked for the European Research Council. In addition to this European community-level funding, each country in the Union has agreed to make subs-


tantial investments, both public and private, in ICST research, aiming to reach the Lisbon target of �% of GNP for R&D by 2010.INRIA’s work is part of this ambitious project to build the European research area.One essential step in increasing recognition of the excellence of INRIA research is having some Institute research scientists participate in projects supported by the European research council, along with outside researchers inte-rested in joining the Institute for a prolonged period on one of its teams. Furthermore, as part of the Cooperation program, the Commission is promoting the creation of “European technology hubs” focusing on stra-tegic subjects such as embedded systems, software and services, satellite communica-tions, etc. INRIA is heavily involved in imple-menting these far-reaching efforts, which will structure European R&D ventures in support of industry.In complement to the Commission’s efforts, initiatives will be implemented with the even-tual goal of founding European-level labo-ratories. To this end, as already discussed, INRIA aims at forming joint project-teams with major research players in several European countries.

2.3.3 FrenchContext

For all areas with growth potential, research is a source of innovation and a driving force for economic development and social progress. It is carried out worldwide, and the competi-tors are heavyweights. France accounts for less than 1% of the world population, and its gross national product represents less than 4% of world GNP. One measure of the international importance of French research is its scientific production, evaluated at 4.7% (the proportion of all global publications that are French, across all disciplines). France is not the country with the highest GNP, nor the most densely populated, and it is not excel-lent in all fields. It is therefore necessary to restate national priorities for fields where we have a strong advantage and which produce the most growth. ICST falls into this category, and doubly so since ICST research not only leads to innovation by its very nature (Internet, digital infrastructures, embedded systems, etc.) but is also essential in developing R&D

in the fields of biology, health, energy and the environment - also stated priorities for our nation. Most developed countries have ICST policies that they are resolutely determined to implement.In fact, ICST is a priority in France, as demons-trated by the resources devoted to the field in 200� by the ANR (€155 M, or 20% of its budget), the AII (€�25 M, or 45% of allocated support) and the DGE (€�8 M, or 45% of support from the FCE for competitiveness cluster projects, in addition to extensive support from local government). To say the least, these are established priorities.Research resources in France are orga-nized around higher education establish-ments, research organizations, companies and resource agencies. Universities and engineering schools conduct their training, research and innovation within large depart-ments studying standard, enduring subjects. Research organizations develop and carry out a research strategy, focus on issues and projects of excellence in partnership with universities and socio-economic players, and ensure that research is consistent with appli-cations, playing a broader role as a driving force in the national community. Funding agencies provide resources for competi-tive programs implementing national policy. This model is currently being established by specialized research organizations, which are currently among the best in the world in their field, and universities which now have tighter governance tools, drawing these partners closer together and increasing their interna-tional visibility and attractiveness.At the same time, the Research Bill has created research and higher education clus-ters (PRES), which are a way to help univer-sities realize their desire of uniting to form a single entity on one site that is visible and attractive worldwide, and Advanced Research Field Networks (RTRA), which despite their vague name serve to provide a framework for international-level teams to form on one single site to study a clearly identified field of research. Both mechanisms bring univer-sities together, creating a structure for better dynamics between universities, engineering schools and research organizations wishing to develop world-class excellence clusters. In this context, it becomes natural and very

2.� The International and National Framework for ICST Research

Context


INRIA intends to use these developments to build a strong position within eight national excellence sites combining research, higher education and innovation, and to help these clusters achieve the highest international levels in ICST..

productive to join forces with competitive-ness clusters for industrial purposes, as they serve as national meeting spaces encouraging synergy between all key players in innovation, industry and SMEs, higher education and research. This promotes innovation on the part of laboratories. As part of its 200�-2009 four-year contract, INRIA intends to continue its development strategy by creating large-scale research centers to provide momentum within inter-nationally visible sites, improving both the quality of research carried out and its impact on industrial development. This strategy was already in place when the government called for candidatures to set up competitiveness clusters and later RTRAs, and is still being pursued as universities adopt new models of governance and the first PRES are being formed.All INRIA research centers play an important role in the competitiveness clusters working on the Institutes’ issues (modeling, complex software, digital infrastructure, data proces-sing, research at the intersection of computer science and life science), whether they are international in scope (Aerospace Valley in Aquitaine and Midi-Pyrénées, System@tic in Île-de-France, Minalogic in Rhône-Alpes and SCS in PACA) or simply have international ambitions (for example in Brittany, Île-de-France, and Nord Pas-de-Calais, the Images and networks, Vehicle of the future, Cap Digital and Trade industry clusters). The Institute’s teams are currently involved in some sixty cluster projects. This partnership policy is also being pursued for ANR operations: the Institute is currently participating in over 120 ANR projects, most of which involve indus-trial partnerships. This level of involvement has been made possible by the quality of the research carried out.In the area of RTRAs, INRIA is a founding member of the Digiteo RTRA in Saclay and the Infectiology RTRA in Lyon. Through its research centers, the Institute should soon be connected to the Mathematical Sciences RTRA in Paris, Agronomical Sciences in Montpellier and Nanosciences in Grenoble. The Institute also aims to form excellence clusters on sites in Rennes, Sophia Antipolis and Paris in the field of Telecommunications Sciences in cooperation with the GET and

the members of the European University in Brittany PRES, the University of Nice - Sophia Antipolis and Eurecom and the PRES currently being formed around Paris �. These three sites will be combining their efforts in an original initiative in their field. Nine PRES were formed in 2007, four of which involved the INRIA research centers in Bordeaux, Lyon, Rennes and Nancy. Others are in the preparation phase, for example in Grenoble, Lille (where a cross-border PRES is being developed), Nice and the Paris region. In keeping with its site policy, the Institute wishes to be associated with these PRES, though the exact form of this association remains to be decided.INRIA intends to use these developments to build a strong position within eight national excellence sites combining research, higher education and innovation, and to help these clusters achieve the highest international levels in ICST.

Inthischapter:

INRIA: Strategic Priorities and Ambitions

3.1 Modeling,Programming,Communicating

andInteracting page41

3.1.1 Modeling,SimulationandOptimization

ofComplexDynamicSystems page42

3.1.2 Programming:securityandreliability

ofcomputingsystems page48

3.1.3 Information,Computation

andCommunicationEverywhere page56

3.1.4 InteractionwithRealandVirtualWorlds page64

3.2 ComputationalSciencesandEngineering page71

3.2.1 ComputationalEngineering page72

3.2.2 ComputationalSciences page78

3.2.3 ComputationalMedicine page88

3.3 SocialConcernsCoveredbyINRIAPriorities page93

3.4 EmergingFields page95

Pr i o r i t i e s


LICST is on the leading edge of a revolution in the methods and tools of investigation, abstraction, modeling, experimentation and design in science and engineering.

The seven priorities of Strategic Plan.

MODELING

PROGRAMMING

COMPUTATIONAL ENGINEERING

COMPUTATIONAL SCIENCES

COMPUTATIONAL MEDICINE

COMMUNICATING

INTERACTING

INRIA is a highly visible international leader in computer science and applied mathematics. Modeling and Programming are among its natural priorities, of which Communication and Interaction are two logical extensions, motivated by scientific and technological needs and by socio-economic concerns. In these four fields, INRIA has based its strategic plan on the following priorities:• modeling: this area focuses on mode-

ling, simulating and optimizing complex dynamic systems, which are addressed through heterogeneous, multi-model and multi-scale representations, combined with resolution and data assimilation methods and high-performance computing tools;

• programming: this area focuses on computer system security and reliabi-lity, aiming to ensure that complex software behaves correctly and that data, commu-nication and exchanges are secure;

• communicating: this area focuses on information, computation and commu-nication everywhere, through ubiquitous systems deployed within new networks, communication and computing infrastruc-tures, through semantic web, services and ambient intelligence;

• interacting: this area focuses on the inte-raction between real and virtual worlds, through several sensory means for the analysis, reconstruction, and understan-ding of the environment, with decision-making, action and interaction in robotics and virtual reality.

These four priorities cover other important areas such as control, optimization and decision-making, which are taken into account in particular for the first and fourth priorities.ICST is on the leading edge of a revolution in the methods and tools of investigation, abstraction, modeling, experimentation and design in science and engineering. Techniques for collecting and using of huge data stores, for simulating, visualizing, virtual prototyping and in-silico experiments are radically trans-forming all sectors of science and technology. INRIA wishes to play an important role in this revolution, whose economic and social stakes are high. This ambition creates three additional priorities, namely computational engineering, computational sciences and computational medicine:• computational engineering: this area

focuses on the design of software and

� INRIA Strategic Priorities and Ambitions

Priorities


Platform for a 3D visual and echograph medical robot — LAGADIC.

embedded systems within physical objects, requiring high levels of flexibility and security;

• computational sciences: this area focuses on ICST’s contribution to several essential interdisciplinary topics in the material sciences, life and environmental sciences;

• computational medicine: this area focuses on the development of models and algo-rithms for medicine and medical biology. The aim is to closely combine the imaging, modeling and data assimilation techniques in order to place ICST at the crossroads of biology and medicine.

These seven priorities define long-term goals and research directions for several years ahead. In order to break down these priorities into concrete, intermediate objectives that

are reachable within the scope of this plan, few “key challenges” are introduced. Theses challenges instantiate the strategic priorities into objectives that INRIA will pursue with its partners. The Institute will make the effort necessary to achieve these objectives, in particular through various incentives (see 4.�.2). These key challenges are not to be seen as deliverables, they correspond to high-risk research objectives. They will illus-trate the Institute’s activities, demonstrate its priorities and provide common ground for its teams. The exact content of each key challenge will be refined as the plan advances and the corresponding research work is launched. Finally, research on the seven priorities will take into account all of their objectives, not just the key challenges chosen to illustrate them.The scientific issues covered by the strategic priorities require increasing investment in experimentation and development activities. The Institute currently has a very strong interest in creating research and support platforms for its development activities. In practice, this ambition is reflected through technology development actions as well as through the expansion of development-specific resources (see 4.�.2). The scientific fields covered by the seven priorities listed above are not indepen-dent. For example, Interacting relies on Communicating: managing the content and semantics of exchanges must begin with communication and be reflected through interaction. Safety issues naturally occur in Programming and Computational Engineering. Modeling is needed in every research activity. It appears in all the priorities, particularly in Computational Engineering, Computational Medicine and Computational Sciences. The connections between priorities can be highly productive because of the cooperation they generate among project-teams. This is particularly the case through the key challenges, since they often overlap over several priorities, although for convenience each key challenge is presented within one priority. Details on the seven priorities are provided in the following sections, with boxes covering the related key challenges and INRIA’s current or desired position for each of these topics.


A brief section is devoted to the social issues touched upon by the priorities of this plan (see �.�). The Institute will also be fostering the emergence of new research topics within its teams that differ substantially from current paradigms in information and communication science and technology. The final section in this chapter is dedicated to these emerging topics.

� INRIA Strategic Priorities and Ambitions

MRI image of the main cortex connection paths — ODYSSEE.

Priorities


3.1Modeling, Programming,

Communicating and Interacting


3.1.1Modeling,SimulationandOptimizationofComplexDynamicSystems

�.1.1 Modeling, Simulation and Optimization of Complex Dynamic Systems

Priorities


One of the major scientific challenges of our times is improving our understanding of the complex systems around us, natural or tech-nological. Modeling large-scale meteorological phenomena, the effects of pollution, flooding, earthquakes and the climate, for example, are impor-tant to society. The same is true of modeling nanosystems, whether in a biological context or for producing circuits using new types of nanocompo-nents. Other significant examples of broad fields of scientific investigation in modeling include the entire cell, the human brain itself, epidemiology, the Internet and major communication software packages. All of these are difficult challenges for applied mathematics and computer science in terms of the modeling, simulation and optimization of complex dynamic systems.


Scientific computing is one of INRIA’s tra-ditional fields of excellence, both for applied mathematics and computational algorithms and for high-performance parallel com-puting. Some forty teams are working in the field, with internationally recognized expertise in the areas concerned. Particu-larly noteworthy are mathematical analysis of partial and mixed differential equation systems (fluid, structural, molecular and circuit dynamics, wave propagation); dis-cretization methods and computational patterns (dynamic and irregular meshing, handling singularities, unilaterality, hete-rogeneity); stochastic modeling; optimiza-tion methods (gradients, combined/mixed, optimal control); automatic derivation; high-performance solvers; distribution and sequencing methods; software and mid-dleware for parallel computing, distributed on a large scale. Many codes and software resources produced by INRIA’s teams are used operationally both

internally and externally, for example in toolboxes for scientific computing itself, support tools for parallelization or implementation on clusters or grids, dedicated software for automatic differen-tiation - such as Tapenade - and meshing.INRIA teams have established a network of close partnerships with scientists in other disciplines. In addition to universities, graduate engineering schools and the CNRS, major organizations such as the CEA, IFREMER, ONERA, and DGA are leading partners for many subjects. Also worth mentioning are the strong relationships which have been forged in some application sectors: with the ENPC through the CERMICS, in ocea-nography with MERCATOR, in meteorology with the LMD, and the IRSN for monitoring air quality (Polyphemus software), as well as with a variety of European laboratories in connection with the SICONOS platform for the study of irregular dynamic systems. The final component is the Institute’s industrial partnerships with Airbus, Alcatel-Lucent, EADS, EDF, FT R&D, STM, Thalès, Total and Turbomeca.

In the future, a special effort will be made to emphasize issues relating to data assimi-lation, inverse problems and multi-scale computing. A special arrangement will be made to actively participate in the simulation programme with ITER.

INRIA’s Position

All complex systems share a certain set of characteristics. Several disciplines must work together in order to study these systems: they involve multiple models and scales in time and/or space; they can be continuous or discrete and irregular. Data on them are highly variable in nature and quality: heterogeneous, noisy and sparse or else plentiful but not always reliable. This makes the problem of connec-ting data with models critical, which justifies the intensive focus on identifying, benchmar-king and assimilating data. Simulating these systems requires substantial research efforts, particularly in computational algorithms. The widespread availability of multi-core proces-sors and GPUs means that both mathematical and computing factors must be accounted for. Predictions from simulations must be carefully assessed for quality given the uncertainty

about data and models. Lastly, optimizing, identifying and controlling these systems are difficult scientific problems. From a mathe-matical point of view, they can be modeled using infinite dimension systems (EDP) or finite (hybrid systems, differential inclusions, variational inequalities) and which are deter-ministic and/or stochastic.Modeling complex dynamic systems is a multi-disciplinary issue resulting from the interaction between mathematics, computer science, automatic control and the disciplines dealing with application challenges and contributing techniques. The main fields involved are: • material sciences, chemistry and physics:

fluid mechanics, plasma physics, materials, propagation of acoustic, electromagnetic or seismic waves, atomic and quantum physics;

Scientific Objectives


Priorities


Modeling: the Challenge of Complexity

• life sciences: molecular dynamics, metabolic networks, gene interactions, cancerology, biochemistry for predicting the effects of drugs, mechanical properties of living tissue, and neuroscience;

• environmental and earth sciences: meteo-rology, climatology, seismology, hydrology, glaciology, oceanography, energy, agronomy and pollution;

• human and social sciences: economic and financial systems, population studies, demo-graphics, epidemiology, distribution networks and transportation;

• engineering: the design and control of embedded systems; mechanical, electronic and computer design of major systems for avionics, space and energy.

Computer science offers its own challenges for applications in this area, for example

in understanding classes of distributed systems communicating asynchronously over a complex network.One initial challenge for research is to bridge the gaps between disciplines to interact in new ways, as has already been done for image assimilation, which involves specia-lists in satellite imaging and computer engi-neers to combine meteorological models. Another factor to consider is the emergence of many application areas, such as the development of circuits based on nano-technology, a major economic objective for the coming years that must integrate an entire hierarchy of models, from atomic physics (nanosciences) to the behavioral model of a processor core, and perhaps even including non-standard mechanics in the case of MEMS.

INRIA’s objective for modeling is two-fold: to pursue research on the most critical subjects while opening the door to new fields deemed to be important in the domain. It is also becoming increasingly necessary to combine models on different scales or of different types. At the same time, stochastic approaches are receiving more attention, both in modeling and as a tool for analyzing deterministic systems. Stochastic filtering is already proving to be an effective tool for data assimilation, but more general approa-ches combining stochastic and deterministic elements need to be developed. Several fields have a very strong interest in such methods, for example geophysics and neurosciences. Finally, although pursuing theoretical research is constantly expanding current approaches to modeling, they are still limited; for example, introducing simplifications into these models at a certain scale can conceal significant effects which are propagated to other scales, and traditional models are sometimes inap-propriate for describing a particular system architecture. In such cases, a viable distinction can no longer be made between modeling and simulation, and calculation methods involving vast quantities of frequently simple, interacting elements must be used: examples

include neural networks, robot populations, multi-agent systems and large hybrid systems. Many specific outstanding questions remain in the research domains associated with these models regarding parameter identification, data assimilation and learning-related opti-mization. In general, a complete methodology for constructing complex models based on elementary components and their theore-tical analysis and calculation has yet to be established. A final point concerns the specifics of modeling for automatic control. The command objective often requires the opposite approach to deve-loping computational models that faithfully reproduce and simulate the complexity of physical and natural phenomena: instead, the aim is to simplify, to extract the main mechanisms of interaction at work in a chan-ging process and to model only the essential elements and ignore anything of merely secon-dary importance, so as to develop effective strategies to achieve a given objective. This need to reduce models to their most impor-tant components poses a genuine scientific challenge when the systems involved are dimensionally or structurally complex.


Optimization: Toward a Cross-

Disciplinary Approach

Simulation: Changing Scales

Simulation of Atlantic ocean flow in the Celtique and Cascogne areas — MOISE.

In simulation, developing new computational schemes is a constant necessity, both to handle the increasing complexity of multi-scale models and to effectively simulate and control irregular dynamic systems. These schemes must be precise with efficient computing times, and be able to run effectively on high-performance computing platforms: multipro-cessor systems, large clusters and large-scale distributed systems. Improving overall perfor-mance in simulating large, complex systems requires both efficient algorithms and the ability to program and make effective use of platforms with very different memory and computing resources. These are the main objectives for the research INRIA intends to undertake. To achieve them, computer scien-tists must cooperate with automatic control specialists and mathematicians to address issues of asynchronous computing as well as node and connection failures. Various meshing and computing tools must also be combined to make multi-model processing effective and to capitalize on software developments. The issue of discretization inevitably requires the subject of meshing to be examined through

the lens of adaptive techniques. Certifying approximations, building robust algorithms and processing data and very large objects at various resolution levels are just a few of the challenges to be met in this field. From the perspective of geometry, problems include representing deformable objects and working in non-Euclidean, multi-dimensional space.In addition, simulations produce large-scale data flows, which can be difficult to exploit. This requires dedicated offline data sear-ching techniques; online, virtual reality or immersion techniques dedicated to scientific visualization must be used for interactive, real-time simulation. Lastly, as a forecasting tool, simulation should also improve management of risk prevention, both by forecasting rare events – a major challenge – and by mana-ging uncertainty. It is particularly vital to look into quantifying prediction uncertainty and to study the sensitivity of results to environmental variations. In general, these concerns with uncertainty must be addressed starting with the data collection phase (inverse problems) and be reflected if necessary in the models themselves.

When optimizing extremely large-scale systems, the robustness of results in the face of uncertainty or minor variations still needs to be improved, especially for PDEs. Furthermore, calculating successive deriva-tives for optimization is still a problem in many cases and automatic derivative methods that have worked for some types of equations must be expanded to very large systems without sacrificing performance in terms of time and accuracy. In general, optimizing multiple entities from different disciplines is still difficult. Optimization itself offers a variety of challenges, for example when continuous and discrete components must be addressed simultaneously, although they require very different methods and ways of thinking. Mixed methodologies must be developed for such situations. When optimizing dynamic systems,

the resistance of solutions to constantly changing input data must be accounted for. Significantly improving optimization efficiency will require a combination of techniques that can continually adapt to slow variations and to failure-detection methods, which serve to improve optimization algorithm efficiency and online derivative estimation. In general, optimization is becoming increasingly impor-tant as an interdisciplinary tool, requiring the Institute to develop its skills in the field.


Priorities


i Simulation and Scientific Visualization for the EnvironmentThe objective of this challenge is to develop and implement a life-size interactive simu-lation and visualization of a complex envi-ronmental problem, for example in clima-tology or oceanology (see 3.2.2). The chosen application will demonstrate the need for complex visualization and interactivity, e.g. in sensor positioning or in managing multi-algorithm simulations. This challenge, which will produce a demonstrator, will require close cooperation between specialists in the environmental sciences and researchers in modeling, simulation, virtual reality, com-puter graphics and intensive computing.

i Fusion Plasma Simulation for the ITER ProgramThe objective of this challenge is to develop a set of 5D gyrokinetic and magneto-hydrodynamic simulation codes for the magnetized plasma models studied in the ITER program. Studying a specific tokamak such as ITER in detail must precisely account for the actual configuration of the plasma balance, which in turn requires the use of a system of specific coordinates called flow coordinates, which respects the isosur-faces of the magnetic field. Using this system, longitudinal and transverse dynamics can be separated, allowing a more realistic dynamic to be used for electrons. This approach, which requires specific computational developments,

will be able to simulate turbulence more accurately. In addition, simulating localized modes at the edge of the plasma is essential to understanding and forecasting energy losses in ITER and validating the approaches suggested to correct them. Currently, there is no program that can simulate the instability of these modes completely. The objective is to develop a high-resolution software solution to simulate a full cycle of instability for edge local modes (ELM) using highly efficient solvers for large, sparse linear systems and high-resolution computational methods on unstructured meshing.

Key Challenges

Fields of Application

Some of the fields currently or potentially affected by this research will be studied specifically by INRIA because of their impor-tant role (see �.1.4). Biological systems on various scales fall into this category, from molecules (biological nanomotors) to organs to gene interaction networks. Typically, multi-scale and multi-model problems occur when trying to fully model complex sub-systems such as cells or the brain. The environment is another main field of investigation, offe-ring challenges such as understanding the connections between ocean and atmos-phere on a global scale, forecasting floods and studying global warming. Here, too, multiple scales are involved in research such as studying ecosystems in close detail. In the field of energy, one subject that will be the focus of further research is large-scale

fusion, combining magnetism and plasma physics. For the technology sector, one of the main challenges for the coming years will be simulating complete circuits based on nanotechnology.


Programming:securityandreliabilityofcomputingsystems

3.1.2

�.1.2 Programming: security and reliability of computing systems

Priorities


With new computational technology, software packages are having an increasingly direct impact on the life of ordinary citizens and the way compa-nies and nations are run. This situation raises many challenges, including:• the security of technical infrastructures (transport, energy), major infor-

mation systems, banking networks, and medical equipment;• the security and confidentiality of infrastructures of a sensitive nature

(defense, government data);• the protection of personal information and private life (medical files,

elections, various private data);• mutual trust in communication between entities and integrity of exchanges; • availability and credibility of various applications (traceability and gua-

rantee of the origin of products, home automation.)In light of these issues, user confidence in digital technologies is crucial in developing and deploying new applications. From the user’s point of view, trust includes a system’s ability to resist attacks and fraudulent use (security), to work correctly under certain conditions (reliability), and to determine liability in the event of malfunction (technical and legal concerns). From the perspective of system and application designers, the technological issues are: providing strong, adequate and proven security solutions; checking applications in advance to ensure that they work cor-rectly; and providing high-performance programming environments that include the production of source code and proof.Since confidence-related technology and services rely heavily on software, INRIA clearly has a role to play in this field. One area for study will be deve-loping reliability and security technology to build user confidence, thus improving authentication and identification, confidentiality, certification, content and personal data protection, traceability and service resilience. Another possibility is exploring new ways to build confidence, for example the emerging fields of electronic evidence used in the legal field, repu-tation-based confidence systems and confidence platforms. This can be more generally described as studying the foundations of safe, mobile, decentralized computing, where data and application access is controlled through managing rights and identities, in the most transparent manner possible for the user.


Rapid progress in technology has also opened the door for new approa-ches in programming and software engineering, such as service-oriented architectures to resolve companies’ concerns regarding reusability, inte-roperability and reducing coupling between the various components of IT systems. Referencing, coordinating and locating these services requires standards, as well as specific protocols to manage transactions and secu-rity within the architecture. This area has yet to be fully explored. The concept of a system of systems has developed at the intersection of software engineering, information and decision-making systems to enable the large-scale integration of systems made up of a large number of stand-alone, heterogeneous hardware, software and human compo-nents, which may be geographically distant from one another but work through the interactions between these components, depending on the system architecture, its changes over time and variations in its environ-ment. Such systems require specific monitoring and a maintenance policy defined during the design phase and adjusted throughout the system’s life cycle. This in turn requires appropriate modeling and simulation techni-ques, as well as assessment and certification methods, if the system is to function reliably.


Priorities


Secure Proof and Programming

Environments

High-level programming languages, type systems and static analysis have done a great deal to improve software reliability. However, there is still a gap between the source code to be executed and the models for this code, used first for design and later for verification. This gap must be reduced, both by developing dedicated programming languages with related code generation and static analysis techno-logy and by using general languages with a broad range of expression and capacity for generic and compositional uses (functional programming, aspect- , contract- , constraint-programming, etc.). The experience of the last few years in deve-loping proofs has revealed new engineering issues. Designing general mathematical languages to describe theories and proofs that a computer can check requires effec-tively integrating computing and deductive capabilities (both are needed major mathe-

matical developments) and building reusable libraries in important areas of mathematics and computer science, including numerical computing, geometry and probabilities. Before proof assistants can be scaled up for adop-tion in an industrial setting, highly automated methods of description, animation and analysis must be developed.Formal methods now allow programmers to establish guarantees of their source codes and models. Extending these guarantees to executable code and its execution requires two additional factors: first, code production and validation tools (compilers, code generators, static analyzers, model-checkers, theorem proving tools) must be certified. Second, a certificate that can later be checked by users of the source code, must be produced and linked to it. Both of these steps require significantly more research before they can be applied in producing real-world software.

INRIA’s priorities for this area relate to two major objectives: • ensuring that complex software behaves

correctly in its hardware environment. The Institute produces reliable development methods based on formal languages, mathe-matical logic, construction of proof, and code and software component verification and certification. The central focus is on key issues such as scaling up, reusing existing code, accounting for all hardware, software,

services and systems components, and inte-grating these techniques into the broader context of software engineering to improve ease of use and expand distribution;

• providing security for data, communica-tion and exchanges between computer systems. Priorities in this area include cryp-tography, security policies and virus protec-tion, all of which are possible solutions to the weaknesses and failures of systems that are increasingly open, distributed and mobile.


The Building Blocks of Security:

Cryptography, Protocols and

Policies

More than 40 project-teams are working on research subjects related to this challenge. It is the main focus of some 20 project-teams. INRIA’s expertise in cryptology, formal methods, proof environments, formal veri-fication of protocols and critical systems is internationally recognized, and the Ins-titute is a world leader in model-driven engineering. This expertise takes the form of designing and distributing high-visi-bility software for proof environments, synchronous and asynchronous program-ming, cryptographic protocol verification, program proving tools and functional lan-guages. These advantages put INRIA in a

good position with its academic and industrial partners (Alcatel, Dassault, France Telecom R&D, ILOG, Microsoft, Thalès, Trusted Logic, Esterel Technologies, etc.) to address challenges of reliability and security which are not only priorities in Europe (for example, the two topics for the 7th FP: Information and communication technologies and Security and space) but also crucial to the independence and sovereignty of nation states worldwide.INRIA is working to expand its industrial relationships, particularly within the AESE and System@tic competitiveness clusters, and its partnership with the DGA. Its goal is to provide expertise and advice on computer security,

which means being attuned to industrial, legal and social expectations relating to risk management, security and privacy in the development of services and companies, confidence platforms and virtualization. To respond to these issues, the Institute has adopted an integrated view of security and safety for software and systems.

INRIA’s Position

High-Performance Methods for

Checking Software and Systems

Despite remarkable progress in formal methods and veri f icat ion techniques through model-checking, formal verifica-tion is not yet scaled to real-world critical systems.Progress will be made by combining the use of tests and existing proofs (verification of models, static analysis, refinement, inte-ractive proofs, test generation) and inte-grating these methods into system design and source code production environments for both software and hardware.Another area to be developed is the incor-

poration of commercially available compo-nents, previously developed software and open-source software: most systems, including systems with high reliability and security requirements, include external components or software. New fields of experimentation have opened for source code verification techniques, including post-developing verification of existing code as well as reverse engineering of code designed for use in secure systems to restore its correctness properties and prove that no residual risk remains.

Creating specifications and designing confi-dence platforms involves security and integrity control mechanisms that connect the hardware to the basic software, mechanisms for making secure the operating system and techniques ensuring that different application classes are safely partitioned. Current solutions are based on the development of proven security micro-kernels and a variety of techniques such as virtualization.

The need for cryptographic primitives whose robustness and compliance has been demons-trated is one of the key points in developing confidence systems. The difficulties in deploying public-key solutions raise different questions regarding how to build and guarantee trust relationships between communicating entities in open, distributed environments. Cryptographic primitives using both symme-tric and asymmetric cryptography must be


Priorities


Data Integrity, Confidentiality

and Privacy

Viruses and Vulnerability

Analysis

improved and validated, new primitives must be developed based on cryptographic principles to ensure that they are robust when deployed, and cryptographic algorithms must be designed which take into account effectiveness (low consumption, speed) and resistance to covert-channel cryptanalysis. Methods for resisting cryptanalysis must also be designed.Cryptographic protocols for new applications such as elections, signature delegation, secure negotiation of security services for multi-level applications and the execution of complex security policies must be proven in terms of their design and their hardware and software implementation. While significant progress has been made in both theories and applications for security

protocol verification techniques, most of the findings apply only to simplified protocols. Addressing complex security protocols in real-world environments is a major challenge. It requires the development of modular proof techniques to demonstrate that the abstrac-tions under consideration are correct with respect to the more precise models used in cryptography, and to formally validate the cryptographic primitives. The need for new security properties handling anonymity and privacy is also growing.One final avenue for promising new research is designing languages to formally express security policies and their properties, and developing methods and tools to check these properties.

The first stage in dealing with cyber-attacks is to analyze and list the security vulnerabilities and weaknesses of software and systems using effective analytical tools. For the verification phase, there is still no solution for handling previously developed components. Although the failure models used for dependability analysis do provide a great deal of inspira-tion, the models for operating and propagating

vulnerabilities are more complex and require specific investigation.The emerging field of computer virology aims to detect viruses and study their propagation, based on static analysis of data or control flows; it also covers designing and building defense strategies, in particular to respond to metamorphic viruses where the program changes each time it infects a new host.

With the increasing quantity of sensitive data stored in databases today, it is becoming urgent to ensure their integrity (authenticity, exhaustivity, up-to-date status), confidentiality (access control) and appropriate use (tracea-bility). Current solutions based on centra-lized administration are difficult to deploy and fail to meet trust requirements for dynamic and distributed environments. Cooperation between database and cryptography research is a highly promising avenue for dynamically establishing trusted relationships between entities in space and time.

Digital technologies and the advent of open systems also generate risks in terms of intel-lectual property and distribution rights. Current technology is able to produce perfect copies of content. Redistribution is easy and difficult to trace. It is therefore necessary to develop new technologies to protect multimedia content: to identify its origin, protect copyrights, check its integrity and trace illicit use. This can be done by inserting into the content an undetectable, inimitable and indelible mark, which must highly robust given the different types of attack to which the signal could be subject.


Risk Control in Open and

Distributed Systems

i Cryptography and Ambient Network Security“Light cryptography” is critical in industrial applications and is needed for low-cost and potentially volatile objects. Developing tra-ceability and object location applications, for example using RFID, requires authentication mechanisms which are easy to implement and inexpensive to deploy but still guarantee an adequate level of security. The goal here is to develop these mechanisms.

i Vulnerabilities, Attacks and DefenseThe focus here is to study attacks and their prevention by conducting significant experiments within a legal framework. The first objective is to identify the security weaknesses and vulnerabilities of software, to analyze and list those vulnerabilities and to develop effective analytical tools. The experiments will also be used to deploy

offensive and defensive systems against mali-cious codes (viruses, worms). They will serve as a first step for detecting loopholes, security auditing and system certification.

i Joint Verification of Reliability and Security PropertiesAlthough reliability and security have been fairly separate up to now, integrated approaches should be developed for a variety of issues, specifically automated verification of security policies (for example for Web services, access control, signature delegation), the design of secure electronic voting protocols and the formalization and verification of their essential security properties.

i Certified Development of Industrial Software ComponentsThe first step in increasing the number of proven software components (compi-lers, certified libraries) used in industry is to provide a platform for designing, modeling and verification of systems and software that takes into account component assembly and the re-use of existing code, so that companies or third party projects can use these tools for real-world cases and supply genuine feedback. The main objective is to demonstrate that the process of critical code certification can be based on a rigorous mathematical approach, spe-cifically by producing a proven compiler which can be used in an industrial setting. The broader objective is to increase the number of proven components used in industry (compilers, verification tools and libraries).

Key Challenges

Risk control is integral to the process of desi-gning software-intensive systems – not only information systems but also critical real-time systems and mass distribution systems. Risks are often identified as failures in or obstacles to availability, security, robustness under peak loads and changes of scale. The perception of these risks has increased as online services based on open and distributed systems are implemented.Many critical and embedded systems are now open systems that coexist and interoperate with information systems. This leaves them vulnerable not only to failures but also to attacks and malware, unexpected user behavior and unspecified or incompletely specified interac-tions between components. In a distributed context, and more generally in

complex environments whose behavior cannot be fully described, it becomes necessary to formalize dysfunctional interactions and express them as constraints to ensure that the system as a whole functions correctly. These formal models may also be used as a basis for establishing legal liability in the event of a malfunction.In mobile ad hoc networks with no fixed infras-tructure, which are often spontaneous and volatile, and which use networks of ubiquitous sensors to interface between the physical envi-ronment and communications and informa-tion infrastructures, security must be carefully examined and ensured before deployment. Distribution of data and computing on the grid also raises new challenges for security, which must be guaranteed even in an environment lacking in reliability.


Priorities



Information,ComputationandCommunicationEverywhere

3.1.3

�.1.� Information, Computation and Communication Everywhere

Priorities


Communication technologies and infrastructures have consis-tently been the focus of many key issues in all civilizations. Digital com-munication technologies have provided a breakthrough in quality and a drastic change in scale. Their economic and social results can now be seen in all business sectors, from the production of goods and servi-ces to health and safety. They are critical in developing an information society (see 2.1). Significant needs have driven the rapid growth and deployment of these technologies: more than 2 billion devices are now connected to the Internet, and an equal number of cell phones are in use, 20% of which have data exchange capabilities. The volume of data that any individual can readily access or produce will soon be quantified in moles* of bytes. Another revolution is occurring in parallel to this growth: the objects we possess now communicate between themselves autonomously to provide us with additional, integrated functions, configuring themselves and adjusting to their environment and to users within a large area of observation (sensor networks) and addressable objects (Internet of things).In order to continue developing, communication technologies must resolve many scientific problems relating to protocols and communi-cation networks, distributed computing and the web of knowledge and services. Together, these three components are used to develop auto-nomous systems of ambient intelligence incorporating processors and sensors distributed throughout space and many everyday objects and capable of reacting to their environment to provide users with access to customized information, knowledge and radically new means of expres-sion and action, at the right time and in the right place.INRIA has consistently emphasized controlling communication services and network infrastructures as one of its priorities. The Institute now has highly developed skills at its disposal as well as a high level international visibility in this field, and has set ambitious scientific goals for networks, computing grids and the semantic Web of knowledge and services.

* By analogy with the chemical unit: one mole = 6,022 x 1023 atoms.


Communication Everywhere

and the Networks of the Future

The Internet of the future is currently the focus of considerable academic and industrial research, as demonstrated major international initiatives such as those of the NSF (FIND, GENI) and DARPA (on wireless technology) in the United States, the European Commission (EIFFEL, FIRE, ARCADIA, EUROFI), Korea (Future Internet Forum) and Japan. In 2007, the French government asked INRIA to supervise a think tank on this subject.Research in this field aims to develop a foun-dation for algorithms and new architectures for communication networks and services that will fix the structural weakness of the Internet, in particular in terms of security, quality of service, mobility, real-time use and intercon-nection with the physical world via networks of sensors. INRIA intends to be actively involved in designing the Internet of the future. The Institute will focus specifically on making the network more secure and robust, facilitating the integration of new technologies such as heterogeneous wireless networks, improving quality of service and implementing higher-level service infrastructures.

New theories of network architecture must be devised to achieve these goals. The protocols and structures controlling this architecture must be reorganized in a coordinated, consis-tent way. Although a great deal of progress has been made over the last ten years, the network layer remains critical for applica-tions with strict requirements in terms of time limits, bandwidth, jitter and reliability. These applications cannot yet be deployed on the Internet. INRIA will perform both theo-retical and experimental research into quality of service and level of service agreements, differentiated routing and routing with quality of service.Our work will also address Internet overlay networks, which enable a large number of peers to interact when participating in a joint task, either as relay points or direct contribu-tors. Research will concentrate on structures that can develop autonomously and in a self-organized manner, such as peer-to-peer systems (P2P) for sharing multimedia files, where group participation is highly dynamic and volatile.

INRIA has three objectives for this strategic priority:• networks of the future: modeling them,

designing their architectures and protocols and overcoming the heterogeneous nature of communication infrastructures to work toward a network which is continuous across space (to respond to the chan-ging magnitude of the number of intercon-nected mobile or fixed devices) and time (to ensure a consistent and transparent quality of service for a wide range of users and uses);

• computing grids: one of the major chal-lenges for distributed computer science in providing vast resources virtually anywhere;

• the Web of knowledge and services: providing access to the semantic content of information available and helping communi-ties of users to use, deploy and integrate an increasingly broad range of applications.

These three areas present common, funda-mental problems in mathematics, communi-cations and information algorithms, which the Institute will continue to be heavily involved in. It will continue its research into several of these fundamental issues, for example quantitative modeling, formal methods for proving protocols, distributed algorithms with partial information, and replication and consensus algorithms. Encoding and infor-mation theory – in particular encoding and compressing images and videos to increase the capacity of mobile ad hoc networks – are important research topics as well. Network and data security are also essential to the content discussed here: confidence, security proofs, confidentiality and privacy, and the protection of multimedia documents. These three areas are detailed below, in addition to the issue of autonomous infras-tructures for communication, computing and information, which affects all of them.


Priorities


INRIA’s Position

Over thirty project-teams are studying subjects related to this priority. In the fields of networks and communication, the Institute has a strong international posi-tion in modeling and metrology. Network standardization efforts are coordinated by the Internet Engineering Task Force (IETF), within which most of the com-panies and laboratories working on the Internet are competing to have new proto-cols adopted. INRIA has long been a very active participant in the IETF, chairing working parties, contributing to MPGs and proposing standards such as UDLR and OLSR. INRIA also participated in the standardization of IEEE 802.11.France has an outstanding industrial environment in the field of networks, as it is home to head office and research

laboratory of Alcatel-Lucent, a key player in the field of network equipment, as well as the head office and main research and development laboratories of Orange, a major European player in wireless access. INRIA has established several joint laboratories: with Orange-FT, in the form of a “collaborative research center”; with Alcatel-Lucent, in the form of “joint strategic operations;” and with Thomson and Philips, in the form of a joint AIR&D laboratory on ambient computing.INRIA is a driving force for distributed computing, computing grids and peer-to-peer systems within the French community, leading several platforms such as GRID-5000. Considerable effort is also being devoted to pervasive computing, which has already generated substantial transfer operations, for example around UbiQ.

Several INRIA researchers and teams wield international influence in the area of databases, knowledge bases and the Web, in particular for XML. Active par-tnerships have been established with the best teams in the world (including UCSD). Transfer operations increase this impact.This position for content, services, uses, and communication must be consolidated even further.

Modeling of the coverage of a network using CDMA protocol antennas — TREC.

In addition, we must better understand and control the Internet as we know it today in order to plan the Internet of the future. INRIA will concentrate on designing new methods of network supervision, measurement and control, Internet tomography, inference of traffic matrices and automatic detection of anomalies.In addition to the Internet itself, our work will also deal with networks of operators, focusing mainly on wireless access and network management.The development of wireless networks depends on fundamental advances in infor-mation theory and coding, innovative algo-rithms and new ideas for architectures. INRIA will continue contributing to the vast effort to build algorithms for better controlling these networks (power, control of admis-sion, access to resources and congestion, and scheduling), in particular using inter-layer optimization. A better understanding of band

sharing for wireless networks, including hybrid networks, is also necessary. The design of network services that provide genuine support without reducing mobility or localization raises important questions. The same is true for the design of wireless video applications, which impose additional constraints in terms of low-complexity or low energy consumption encoding techniques.Networks have recently been increasing in complexity, dynamicity and heterogeneity of networks, which makes them more difficult to manage. They demand new architectural and distributed algorithm models to be designed so that fault, configuration, cost, performance and security management mechanisms can be implemented in an autonomous, reliable and robust way. The ability to scale and the functional impact of network management imperatives are crucial, especially for optical networks in which reconfigurable components will enable operators to meet demand on a


i Design and Evaluation of New Internet ArchitecturesFor the past thirty years, the Internet has been changing gradually in ways that are compatible with what already exists. This approach has unquestionably been suc-cessful, but it has reached its limits since it cannot resolve major structural problems in terms of security, continuity of service on heterogeneous infrastructures, robus-tness in transition, and observation and diagnosis tools. This key challenge involves exploring new network architectures which are radically different from those already in existence. The objective is to design architectural components that provide native, secure support for services such as data distri-bution, peer-to-peer data sharing and automatic diagnosis. These new architec-tures must also be evaluated before being deployed on a large scale. This requires realistic, easy-to-configure simulation plat-forms that can control experimental and comparative analysis conditions involving real users. Simulations must include better models and real source code. Their limits

must be identified and circumscribed. Finally, experimental and simulation platforms must be integrated to simplify the design and eva-luation of new architectures. The aim here will therefore be to develop a platform and evaluation methods, including a simulator such as NS3 and an experimental platform such as OneLab.

i Experimental GridsThe challenge here involves demonstra-ting ambitious up-scaling of programming techniques for computing grids by carrying out several dimensioning experiments on the Grid’5000 infrastructure developed by the ALADDIN initiative. The experiments will use a grid infrastructure to specifically address large-scale generic combinatorial optimization problems that have never been solved. Experiments will also be performed in the field of structural biology, such as the problem of anchoring large molecules. These and other experiments will be conducted on several thousand processors on several sites to provide experimental validation for scaling up with significant gains in robustness and performance.

i Services and UsesThe aim here is to provide intelligent answers to queries on the Web using semantic data content, for example in collaborative work where information will be incorporated and presented to users who will be able to interact with the intermediate results and thus help to structure the final response to the request. These new services must be designed to allow analysis of their effec-tive uses: appearance of communities and social networks, dynamic construction of individual and collective profiles, detection of trends, diagnosis of performance and quality of service. As information about uses is being produced more and more quickly and from an increasing number of sources, data flow analysis must be possible, which implies extracting knowledge, inter-preting it and managing its changes.

Key Challenges

terabyte scale, and which will require high-performance, programmable control methods capable of scheduling network resources in real time.Finally, self-organized networks must also be addressed. INRIA will focus its research on ad hoc networks, hybrid wire-less networks, spontaneous information systems and networks tolerating time limits where intermittent connectivity is typical Most of these networks are based on “multihop” routing, which consists of using other termi-nals or components in the network as relays to transmit information. The Institute will

continue to study new distributed control algorithms for such networks, particularly for accessing shared radio channels, routing, admission and congestion control and consumption control. The general concept requires distributed algorithms enabling users to be constantly connected, as effectively and fairly as possible, particularly for flexible radios. Research into economic models will focus on developing new ways to deploy and integrate management functions through models such as the use of incentives, game theory and cooperative and collaborative approaches.


Priorities


Computation Everywhere

Information Everywhere

and the Web of Knowledge and Services

Computer cluster at INRIA Rennes Research Center.

Communication networks and micropro-cessor technology have progressed to the point that the computing power available to a user is no longer limited locally to a single machine, but can draw upon vast resources available at low cost and distributed on a large scale. The aim of ubiquitous computing is to make these resources easily accessible everywhere, at any time, in a transparent and reliable way. Computing grids, one of the major challenges of distributed computer science, raise specific issues relating to middleware, operating systems, resource management and programming models.Distributed middleware is a software layer above operating systems that facilitates deployment of an application on networked machines. Designing it raises questions of heterogeneity management, changing availa-bility of resources and the transition from client/server organization to peer-to-peer architectures. In addition, existing middleware has a one-way relationship with applica-tions that does not allow for negotiation. This handicap can be overcome if applications are able to exploit the nature and topology of resources and specify the communication patterns they use in advance.In the future, operating systems may handle some of the functions of middleware and offer better performance. This applies speci-

fically to designing network-based operating systems, providing distributed management of a domain and enabling better separation of applications and the underlying infrastructure through virtualization and abstraction.Resource management can no longer be local; it must work in the context of widely distributed resources. This means that, for some applications, data flow management must fit into communication constraints, which are difficult to predict and can become more restrictive than computing resource constraints. Good resource availability models must be developed that are able to adapt to substantial changes as computing nodes appear and disappear during processing. The Institute will also focus on management mechanisms offering guaranteed performance, for example in designing efficient, predictable and reliable end-to-end protocols for the transfer of large data collections.Finally, new programming models are needed to efficiently use the grids. The intrinsic complexity of distributed processes on hete-rogeneous and forward-compatible resources must be taken into account, for example by specifying the characteristics of the appli-cation that relate to those of the computing infrastructure. New programming paradigms inspired by nature and chemistry must also be explored.

Transitioning to a web of knowledge and services requires the ability to control substan-tial volumes of heterogeneous data (structured data, text and multimedia documents, online services) and the development of new func-tions relating to data content and the high-level needs of individual users and communities.Access to semantic content depends on the convergent development of two types of complementary approaches: • those based on XML and related languages,

in particular RDF (“resource description framework,” allowing for metadata intero-perability) for structured documents and data;

• those of the semantic Web used to express and exploit knowledge.

Our research will focus specifically on the representation of knowledge, as well as on learning and on the automatic processing of natural language, to develop ontological and semantic annotations that will clarify contexts, and their use in queries and data management. This management also requires merging information from multiple, hetero-geneous sources, which in turn requires the relevant resources to be acquired, understood and monitored so that they can be enhanced (qualification, semantic indexing) and cohe-rently integrated. Online services can provide sources of active information; the compo-sition of web services relies on planning and learning techniques. Data searching and monitoring are most relevant in connection with


Communication, Computation

and Autonomous Service

Infrastructures

semantic content, thus requiring substantial progress in developing and integrating several techniques, including statistics, linguistics and the extraction of semantic information from multimedia documents.It is essential to recall that users of the web of knowledge and services are not passive readers. They are key players within a commu-nity, producers of knowledge, services and even goods within a collaborative space. This

role touches on the issue of basic functions of communication, interaction and interope-rability on the semantic level, which will be discussed further in the following section on social interaction and mediation (see �.1.4). Another connection with the following section is ambient intelligence systems, in which many interconnected devices perceive and interpret their environment to interact with one another and provide users with the means to act.

Autonomous information systems are a central concept in addressing the problems posed by an increasing demand for acces-sible, sustainable resources at all times and in all places. Such systems comprise a collection of components that adjust their internal beha-vior and interrelations according to high-level rules. One challenge is developing effective solutions that can implement some or all of the key characteristics of such very large-scale distributed communication, compu-ting and information management systems. The characteristics to be observed are self-supervision (knowledge by the system of its own status and behavior) and self-protection (detecting both internal and external attacks and protecting its resources while maintaining the system’s overall security and integrity). These systems must also have the capacity

for self-optimization (detecting deterioration of performance and optimizing their beha-vior accordingly), self-correction (diagnosing potential problems and reconfiguring them-selves in order to continue functioning) and self-configuration (dynamically adjusting their resources according to their own status and that of their operating environment). They must adapt to their conditions easily (be able to observe their environment and react to changes in it), be open (portability onto various hardware and software architectures, use of standard and open protocols and interfaces), and be able to effectively anticipate their own needs and behaviors as dictated by their operating situation and behave proactively. Research into these subjects will cover quali-tative and quantitative modeling, supervision, diagnosis, reconfiguration and planning.


Priorities

��Strategic Plan 2008-2012


1.1 From Inception to the Late 1990s

InteractionwithRealandVirtualWorlds

3.1.4

�.1.4 Interaction with Real and Virtual Worlds

Priorities


A tool is an extension of the hand. Tools derived from information technology also increase man’s sensory, motor and cognitive capacities. Several forms of inte-raction with the physical world, with computational models or in social mediation arise through the use of such tools, directly or remotely when the tool becomes auto-nomous. The scientific problems posed by the design of these sensory-motor and cognitive extensions to humans, and by related interaction mechanisms are major topics for research. Examples of the type of problems to be investigated include:• how to detect and interpret sensory information to recognize objects, understand scenes and behaviors using several different senses: vision, hearing, touch and smell; • how to represent, reconstruct and visualize data and simulations, enable data to be explored visually and manipulated, and take part in virtual scenarios by rendering the computing tool invisible in the interaction;• how to represent and use symbolic and linguistic information to obtain and supply information, exchange and generate knowledge;• how to act autonomously and deliberately in completing a task, perceiving and modeling the environment, deciding and planning actions and improving behavior by learning.INRIA is heavily involved in these scientific topics. It aims at making significant contributions, since the scientific, social and applicative stakes are high in many sectors. For example, interactions with the real world involve the use of robotics applications in hostile environments and difficult tasks (mines, building sites, deep-sea and planetary exploration, demining, etc.), service robotics (surveillance, han-dling goods, cleaning cold rooms and clean rooms, etc.), transportation and driving assistance systems, “intelligent” roads and safe cities. Other applications include home automation applications, applications to assist reduced-autonomy individuals, and personal automation (domestic assistance, recreational machines, and robots or robotic functions to be used by humans). Medical robotics (see 3.2.3) raises sensitive public health issues.Virtual interactions meet very important needs. In medicine, for example, it would be advantageous to be able to examine and feel a computational heart, built from medical imaging models and data, through a haptic device. Teaching and training are prime fields of application for virtual reality, immersive and interactive environments. Visual and multimedia flow interpretation involves many interdisciplinary issues, including the safety of goods and individuals. The leisure economy, a burgeoning

�� Strategic Plan 2008-2012

industry, relies on perception and interaction (video games, film design, ubiquitous communication, etc.), appropriate assistance for broad access to multimedia servi-ces and information on the Web, and geo-localized, personalized information. Com-putational engineering throughout the life-cycle of a product or complex industrial or urban installation involves visualization and virtual reality within collaborative design techniques, often requiring behavioral models for human users. At last, techniques for visualization and interaction using sophisticated computational models that can manage complex simulations may become accessible to a very broad public. From a social point of view, these tools must be used effectively, enabling everyone to prac-tice hands-on science so that science becomes popular again, and they must bring scientific debate back to the forefront of social concerns.

Interaction occurs when two or more entities actively exchange information and influence each other, and it requires mechanisms for perception, action and comprehension. Before turning to the specific objectives for real and virtual interaction, we will discuss the objec-tives common to all the scientific topics dealt with here. These objectives relate first and foremost to sensory modes: developing analytical, reco-gnition, categorization and semantic interpre-tation capabilities that use vision or hearing in speech and natural language interactions. Currently, there is no effective way to analyze complex sound tracks in detail based on a recording with only a few sensors. Processing and understanding natural languages are major challenges for computer science; natural language is an essential vector of communi-cation for exchanges involving high semantic content. For vision, areas for progress include robustness, adaptation to lighting changes and the condition of sensors. The key is to establish a link between semantics and the scenes observed. Other objectives relate to the synthesis of sensory feedback from models

and data. Multi-sensory fusion, for analysis or synthesis, combines the methods already mentioned and also touches on feedback, the interpretation of movements, attitudes and behavior, as well as the link between the various senses and natural language.Action-related problems vary from the command loop hinging on perception, to decision-making, planning and learning. The dynamic environmental modeling required for perception and action raises further, as yet unresolved problems.New, higher performance human-machine interfaces are needed to make the computer invisible for the user and enrich interaction potential. This involves designing sensory interfaces based on the five senses and able to analyze expressions, movements, tone of voice and gaze. Designing completely or partially immersive systems that combine multimodal tactile, touch and sound interfaces, inclu-ding communication and location capabili-ties (for example in “wearable computing”), is a true challenge. It is compounded by the need to study humans themselves, both using sensory-motor models and from a cognitive and


Priorities


INRIA has the resources to rise to these challenges. All of the disciplines mentio-ned above are already actively pursued within the Institute, with some thirty project-teams focusing their research on them. Another twenty are also making some contribution through their work. The Institute is on the front lines inter-nationally, both in terms of mass and quality, in the field of computer vision, and the same holds true for computational geometry. In computer graphics, INRIA’s teams have also proven their excellence and represent the strongest core team in Europe in the field. INRIA has a high-quality critical mass in robotics, speci-fically for cutting-edge work on parallel robots and the control of nonholonomic systems. The Institute also has advan-ced skills in natural language and speech processing.

For robotics, INRIA’s teams rely heavily on applied mathematics for vision and for gra-phics, as well as on real-time computing and formal specifications. They work together actively on projects combining perception and computer-generated images, perception and robotics. They also collaborate closely with experts in cognitive sciences and neu-rosciences.INRIA’s strong, long-standing commitment to the field of graphics and images has given rise to many academic and industrial par-tnerships. In France and in Europe, it works with the main industrial players in the field (for example, Thales, Philips, EADS and Renault), as well as video game manufactu-rers, banks and the RATP transport authority (for video surveillance) and post-production companies. RIIT networks have been heavily involved; INRIA also participates actively to several competitiveness clusters (Images and

Networks and System@tic in particular). The Institute has strong ties to the CEA, FT R&D, INA and CSTB, and cooperates closely with its start-up companies. Far-reaching European partnerships suppor-ted by FP programs are also working in the field. Lastly, formal collaboration through bilateral and multilateral pro-grams, associated teams, and informal collaboration with the best teams in the world (MIT-Csail, UCSD, etc.) demons-trate that INRIA holds a prominent inter-national position in this area.In the future, particular effort will be concentrated on new interfaces, including brain-machine interfaces, and on incor-porating semantics and other human and social factors.

INRIA’s Position

Similarity search in image databases with IKONA — IMEDIA.

behavioral point of view. New means of direct brain-machine interaction pose both scientific and ethical problems requiring close collabo-ration with neurosciences and the designers of brain activity measurement technologies.If we are to solve these problems, we must develop more advanced algorithms in a number of areas, such as:• semantic interpretation and learning, achieved

using statistical and probabilistic techniques for signal processing, speech and images, to describe heterogeneous flows and distin-guish between sources;

• geometric and image processing algo-rithms, for vision, environmental modeling and planning;

• computational techniques, in meshing and structuring of virtual reality data, multi-sensory fusion and environmental modeling;

• natural language processing algorithms;• decision-making and planning algorithms.Of course, several of these techniques are the basis for developing robust methods of perception, action and interaction. In turn, their integration raises questions of computing architecture, distribution and organization of high computing power.It is essential to emphasize the interdiscipli-nary nature of these challenges, which require the contributions of ICST and neuroscience, cognitive science and the human and social sciences.


Robotics and Interaction

with the Physical World

Interaction with Virtual Worlds

Biped walk control — BIPOP & DEMAR.

In this area, the major challenge is to combine the diversity of tasks that may be accomplished autonomously by a machine with the variability of open environments in which a machine may act efficiently. Effectively achieving this relies on robust commands, environmental modeling, reliable and rich perception, planning and dynamic learning and desi-gning reliable, high-performance, modular computing architectures. The techniques already mentioned can be used to meet this challenge, along with models from cognitive sciences and the design of controllable self-organized systems. In all cases, integration is the core of the scientific problem: integrating perception and movement, planning and action, lear-ning and exploration. Performing assignments and tasks through interaction with an autonomous system requires recognizing movement and human

attitudes and behavior, and in particular allowing for example-based program-ming. For users, remote exploration of the physical world using a machine requires dynamic synthesis of an enhanced reality, which raises new problems of sensory feedback, perception and modeling that are distinct from the problem of tasks completed by machines alone.Somewhat closer to home is the concept of direct interaction, or the “enhanced human”, which could be equipped with such devices as exoskeletons, ortheses and prostheses, as well as a range of proprioceptive and exteroceptive sensors (in particular for geo-localization). Scientific problems in this field relate to algorithmic and automatic control; they involve proces-sing signals from sensors to supply data on the operator’s attitude and movement intentions, and closed-loop control, which involves high security considerations.

Creating and managing virtual and enhanced worlds has already combined graphics and computer vision. The computing possibilities available enable us to create and view complex, multi-scale information, in quantities too large to be easily grasped. New methods of visuali-zation using geometric and functional modeling are needed to fully use the data from scientific computing or data mining. Algorithms must be significantly enhanced for interactive use.Motion sensor techniques must be improved for the use of animation techniques; for example, the need for markers must be eliminated. Visual, auditory and haptic multimodal rendering must be able to rapidly co-locate a host of sensory data; extensive research is required to improve realism and readability. Providing and acces-sing ubiquitous computing resources means adapting to the limits and variability of these resources. In addition, �D interaction with virtual universes must develop and incorporate a better unders-tanding of users (physiological and psycholo-gical studies, biomechanical models, behavioral models and virtual tasks). This will help to improve multimodal 3D interaction (obtaining

effective spatial and temporal co-location of multiple sources of sensory data), mobile 3D interaction (the ability to move around the virtual universe with maximum freedom of movement and to work from outside of rooms containing expensive equipment), collaborative 3D interaction (collaboration between partici-pants equipped with different peripheral devices which may have complementary objectives), and finally cognitive 3D interaction (accessing and managing semantic information about objects in a virtual scenario, and working on the mental representations and intentions of the user, for example through brain-computer inter-faces). Globally, interaction techniques must be able to adapt to complex parameters including the context, difficulty and level of completion of the task to be accomplished, as well as users’ physical and cognitive capabilities. Multi-scale techniques must be developed, not only for structuring a virtual environment to address graphic rendering problems, but also for �D interaction itself. The many possible fields of application include designing, producing and maintaining manufactured goods and training for technical as well as more cognitive tasks.


Priorities


Social Interaction

GRIMAGE, a virtual reality platform at INRIA Grenoble Research Center.

Perception and synthesis open up new possi-bilities for interactions between individuals and social mediation. For example, the virtual or physical avatar of a remote person may participate in a collaborative activity or in new situated learning methods during the course of normal professional situations. Within private social networks, people may wish to maintain the same social contact they have in person when they are physically remote. This requires the development of light, easy-to-use communication methods that indicate when the other person is present. They could signi-ficantly improve the independence of elderly or disabled individuals. Another possible application might involve several remote individuals exploring and creating the same virtual environment together for engineering requirements, artistic purposes or leisure. Still another could revolve around a large-scale social simulation such as Second Life, where individuals exist virtually with a high degree of freedom, enabling them to create, produce and interact in a parallel economy that also has an effect on the real economy.Many new tools, new services and very open-ended new uses now rely on a very large community of hundreds of millions of internet users and on rapidly changing modes of interaction. The possibilities for expression, design and creation are increasing rapidly as inexpensive tools offer increasingly rich graphical possibilities and image capture, geo-localization, communication and computing resources become available in conjunction with software to input and efficiently process multiple services. The notion of collective intelligence, introduced by programmers’ forums to build shared experience, is illustrated by Wikipedia, an encyclopedia with over 10 million articles in 250 languages. This concept is now taking on practical dimensions in all sectors: geogra-phic exploration and the classification of planets and stars for the largest astronomical catalogue ever designed; expert services and technical problem-solving via enginee-ring, design and functional test services for new products; marketing and simulation services and large-scale economic, political and social studies. The companies behind these new types of services rely on larger and larger communities, creating new forms

of working relationships. This new type of relationship will also affect associative and political relationships.It is not hard to foresee that as today’s sensory interaction capabilities are made increasingly richer and more natural, such applications will improve in both quality and quantity, expanding collective intelligence and the use of social mediation. This opens many new fields of research with respect to designing, developing theories and expe-rimenting with the uses provided by such forms of mediation. INRIA wishes to form partnerships, especially with researchers in the human and social sciences, to contribute to solving them.


i Real-Time Semantic categorizationThe challenge here is to devise a portable vision system able to categorize seman-tically the contents of an indoor scene in real time and interpret the actions of people as they move. Consider a video camera operator filming a room: users may wish to interpret the video stream in light of the objects in the room, their spatial relationships, the type of scene being viewed and the activities taking place. INRIA’s teams are currently deve-loping geometric and statistical models of images, objects, scenes and actions to serve as the words and grammar of this language, techniques for learning models in categories of interest, and efficient methods for finding instances of these models in image databases, video and perhaps audio streams. Problems include the natural variability of the shape and the appearance of the objects in the scene, the characteristic difficulty of building a “visual language” and the volume of data to be handled.

i Multimodal Consultation of Multimedia DataIt is still fairly difficult to access selectively the enormous volumes of information available over the Web. The document as the main search unit, is not precise enough. Search engines do not correctly process requests on semantic content, and

usually consider only the textual component of documents. The challenge here is to make use of entire documents and to obtain answers to questions asked in natural language, written or oral, without using requests that presup-pose partial knowledge of the answer. This will involve users in an interactive, learning-based consultation process, customize searches, and consider the context of the request, for example to give more focused answers for business consultations by specialists. We wish to be able to exploit all intelligible results (not just complete documents), supported by references determining their relevancy, and to significantly improve the performance of online access to multimedia documents with audio, musical, language and video components (recordings of meetings, radio and television programs, texts) in terms of the interfaces used (interrogation modes, delivery of results) and the volumes processed.

i Independence for the Elderly and Disabled How can elderly and disabled persons live more independently? This may require assis-tance with mobility and daily tasks, methods of surveillance and easy and natural inte-raction with loved ones, and a heightened sense of belonging to a family or professional community. Many challenges involve techno-logy for actuators and relatively non-invasive sensors (audio, visual and biomedical) that can be worn by people or else fixed or mobile

in indoor and outdoor environments, as well as open architectures that are easy for untrained individuals to reconfigure and use. One or several research actions aimed at significant demonstrations will be conducted for this challenge.

i Assistance and Service Robotics in a Human Environmentenvironment. Such systems can be deployed in various contexts such as towns, public places and homes to supply services such as domestic help and assis-tance with mobility. These systems must be able to learn, adapt, and interact naturally and ergonomically in an open and constantly changing envi-ronment. They must functionally integrate perception/action loops, modeling, control/command and cognitive functions. Their design must take into account the constraints of robustness, operating safety, and uncer-tainty management. Scientific work for this challenge will focus on these various func-tions that occur in the human environment and seek to integrate them with cognitive demands, modeling and commands.From an experimental point of view, this challenge will lead to demonstrations in realistic contexts, such as assistance for movement in public places, including fixed infrastructures (cooperative or enhanced environment) and heteroge-neous robotic technologies.

Key Challenges


Priorities


3.2Computational Sciences

and Engineering

Science and engineering methods and tools for modeling, experimenting and designing are changing radically, as exemplified in the in-silico experiments and virtual prototyping approaches. This results from the developments of representations and algorithms for modeling, simulation, imaging, signal processing and visualization. To contribute to these developments, INRIA has three strategic priorities for:• Computational Engineering;• Computational Sciences;• Computational Medicine.These three priorities represent an ambitious goal for ICST in the advancement of science and technology. It is an interdisciplinary ambition covering several scientific fields to which the Institute will contribute, in its own domain, in partnership with other organizations. Integrative research actions will be encouraged, particularly in computational medicine, where the objective is to bridge the gap from biology to medical technology.These three priorities correspond to distinct but overlapping focuses. The life sciences are naturally present in computational sciences, in cellular biology, animal and plant biology and bioinformatics, while an integrated perspective naturally includes medical biology in computational medicine. Medical technology also includes a clear engineering component. The dividing lines between these three priorities should not be over-simplified. Topics such as computational neuroscience, for example, which have been included in the third priority due to the large number of medical applications involved, are also highly relevant in computational sciences.Finally, the links between these three priorities and the four preceding ones, on Modeling, Programming, Communication and Interaction, are very productive, particularly in defining certain challenges.


ComputationalEngineering

3.2.1

�.2.1 Computational Engineering

Priorities


Most manufactured items now exist computationally before they exist materially. This computational design was initially focused on the geometry of an object’s parts (CAD models). Today, computational engineering has to move further towards multi-physical (mechanical, electrical, thermal) and functional models for each component of an object to be designed, and towards the composition of the components models into a global design according to the object’s overall functio-nal, non-functional (reliability, safety, maintainability, cost) and life-cycle properties (the so-called Product Life Cycle Management approach). This ambition raises major challenges for designing and developing complete computational specifications for an object, from the drawing up of the initial models to their implementing in simula-tion, optimization, virtual prototyping, testing and qualification, up to the automatic synthesis of software controlling the object’s production and behavior.Many everyday objects and all complex systems include software and processors that use sensors, actuators and communication capabilities to extend the object’s functions, improve its performance and operating conditions, and meet require-ments in terms of safety, ergonomics, mobility, robustness and reliability. Only 2% of the 1010 processors (CPUs) sold in 2005 were in computers; 98% were imbedded into various other objects. Many chemical and physical sensors – gas, pressure, temperature, acceleration, distance, video, and RFID labels – are embedded in cir-cuits along with processing and signal transmission units. Likewise, an increasing number of actuators are available, embedded in gear mechanisms, sensors, com-putational and energy management controllers. More and more, objects are capable of wireless communication and able to communicate and function in a distributed mode. These software and hardware components, implemented in an object, are embedded systems. They are embedded in transportation systems (avionics and space systems, of course, as well as rail transportation and cars), in everyday objects (home automation, household, cultural and leisure equipment) and in industrial and medical equipment; people can also wear them.


Some fifteen INRIA project-teams are heavily involved and highly visible in these research topics. In the field of syn-chronous languages, the “French school”, within INRIA especially, has made many outstanding scientific contributions, including some which have led to such high-value spin-offs as Esterel Techno-logies and TNI-Software. The Institute is also successful in other fields such as compilation and formal methods, and has produced many high-quality software packages such as the CADP toolbox.Another area of INRIA involvement is automatic control and computing for modeling, in particular dynamic systems.

In this area, the Institute’s teams benefit from the Scilab-Scicos chain, which covers everything from computing to simulation and can be extended with Syndex to code synthesis for various architectural confi-gurations.The Institute also participates in competi-tiveness clusters dedicated to applications for embedded systems. Some of the most important include Aerospace Valley, focusing on avionics and space systems, System@tic, for embedded systems in automobiles, Minalogic, which addresses problems on the scale of microsystems (SoC), and SCS for traceability, RFID and security. In Europe, the Institute is involved in several joint

projects, some of which fall under the ARTEMISIA initiative.The very computer science and automatic control communities have traditionally claimed the fields of fault detection, quantitative risk assessment, the relia-bility of instrumented and programmed systems, safe system design processes, supervision, diagnosis, adaptation and reconfiguration techniques for deployed systems and prevention and protection against computer attacks. Joint work in this area must be fostered and encouraged in order to provide solutions with signifi-cantly better performance than those that either community could create alone.

INRIA’s Position

INRIA wishes to support the development of computational engineering throughout the entire design and life cycle of an object. This involves establishing the basic building blocks for a global engineering approach, from modeling the object, its functions and desired behavior and its architectural design, to virtual prototyping and synthesizing its embedded software. This ambition is consistent with vital economic issues for industry in France and Europe. It is based on the previous priorities, in particular with respect to:• modeling: physical (mechanical, elec-

trical, hydraulic, thermal, etc.), dynamic and command models;

• programming: formal programming and proof techniques, compilation, source code synthesis, reliability, safety, harmlessness;

• communication: distributed high perfor-mance data and computing, collaborative design;

• interactions: signal and image processing, visualization, virtual reality, interfaces to support design.

The Institute aims to combine these four avenues for the development of compu-tational engineering targeting software

and embedded systems. The main focus in achieving this objective will be on systems embedded onboard physical objects, which rely heavily on computational engineering, with high constraints in terms of critical behavior, dynamics and safety. This cate-gory of problems, of interest to automatic control specialists and computer scientists, is particularly relevant for all transportation systems.To clarify our objectives, we will discuss several essential functions in the following section: models of the physical object, the architecture of the embedded system, software synthesis, validation and verification, and the object’s life-cycle. Computational engineering requires that all of these func-tions be highly integrated, which is one of the scientific and technical challenges in this area, in particular when co-designing hardware and software. Industrial partnership is the natural extension of interdisciplinary partnership, and it is crucial for the twin prio-rities of computational science and medicine. INRIA will develop roadmaps and take indus-trial imperatives into account in its scientific strategy, including essential international standards in this area.


Priorities


Designing and Modeling

Physical Objects

Embedded System

Architecture

CYBERCAR, a fully automated city vehicle at INRIA Rocquencourt Research Center.

Designing and modeling physical objects requires the integration of multi-physical (mechanical, electrical, thermal, electro-magnetic) models of the object and of its desired behavior, reliability and security in a multi-level simulation that can predict its properties and accomplish the initial stages of virtual prototyping.The difficulties are the same as those of multi-physical and multi-scale modeling. Integration of component models for the object creates its own challenges. Of course,

complex objects are based on designs which combine or even reuse existing compo-nents. In order to do this, a description of the components and the block diagrams showing how these components are arrayed must be associated with specific properties of composition. A new component concept will be needed for automatic control showing how to assemble closed control loops while maintaining the correct properties for the entire object (stability is not a compositional property).

Embedded system architecture has several aspects: the communication and computa-tion model, the combined specifications and design of hardware and software components for the embedded system, the elements ensuring fault tolerance, operating systems and associated executables. One basic problem involves resolving the various temporal mechanisms used in communications: synchronous, asynchro-nous, sampled, and perhaps at different levels of the architecture in hybrid communication models. The resulting properties, for example in terms of blocking or non-blocking commu-nications, impose significant constraints on embedded software engineering. These temporal mechanisms are at the heart of embedded operating systems, which pose specific problems.Currently, a radical change in processor architec-ture is underway: their performance is improving by adding more cores rather than accelerating clock speed. This technological change has led to component-hosted parallelism and has had a general impact on programming and software architecture. Its effects have been especially noticeable in embedded systems, with potential gains in specialized proces-sing, performance and safety. These changes have opened wide avenues for research into programming and code compilation for these new processors, highlighting the need for an innovative way to reconcile demands for relia-bility and performance in real-time embedded systems with the increasing non-determinism of the architectures on which they rely (and

in particular the non-determinism inherent to multicore processors).Of course, architecture affects an object’s overall functional properties. For example, the robustness of command laws depends on control distribution characteristics: the impact of latency, jitter and perhaps loss. These in turn affect non-functional properties, such as dependability, resources (dissipated energy), maintainability, the cost of production and use of the object. Command techniques based on automatic control can be used to actively control certain significant variables (sampling, communication modes, scheduling, power) in situations with limited resources.All of these issues must be studied in order to move toward a computational enginee-ring environment with which designers can explore a design space providing different architectural options: the communication model, number and performance of proces-sors, software organization, task scheduling, etc. A method must be developed for compa-ring these architectural options with one another and to specifications and means to assess them. This requires precise metrics, which is a significant and still largely an open problem.


Software Validation and

Verification

Dependability and Security

Embedded Software

Synthesis

Computational engineering uses the models developed in the previous design stages to produce executable codes that conform to system specifications. Moving from automatic control and computational simulation models to embedded code is one specific, central goal for this priority. Given the critical nature of the systems concerned, it is essential to the scientific objectives being developed in the area of programming. Other objectives are more specific and include the following:• compilation techniques that meet the specific

constraints of embedded applications, for example limited response time or low energy

consumption, and that respond to the unique characteristics of processors and architec-ture, especially multicore architecture, for which parallel processing should be occurring automatically;

• algorithm synthesis for certified source code;• the static nature of many embedded codes,

with a fixed memory allocation, which simpli-fies verification.

Lastly, it is important to emphasize that software synthesis is closely linked with hardware and system architecture synthesis. This is particularly relevant for the design of Systems-On-Chips (SoCs).

One issue in this area involves verifying the functional properties of a physical object based on the models previously described, and in particular verifying its dynamic beha-vior. The development of tests to accomplish this verification is a problem for automatic control; it has received little attention to date and remains essentially unresolved.A second problem specific to computer science involves verifying software proper-

ties using model checking, static analysis, and abstract interpretation methods, whose performance and scope need to be expanded. Both source codes and object code must be checked. Given this requirement, developing certified compilers and machines is an impor-tant objective.The verification of non-functional properties, in particular dependability, raises other funda-mental problems that are dealt with below.

The requirements for dependability and compliance with reference standards have a considerable impact on embedded system architectures. INRIA’s contribution to these areas comes in the form of formal specification methods and proof-based engineering. Architects of complex systems understand the importance and the difficulty of speci-fying conditions for logically and temporally correct execution. Specifications must take into account elements such as:• distributed-system fault models (lost

messages, arcane breakdowns in processing components, asynchronous behavior);

• hardware platforms that are increasingly complex and include local components with non-deterministic behavior;

• placements and routings on these new non-deterministic hardware architectures;

• specific data protection requirements in the event of attacks or malfunction (the “fail securely” principle).

There is still no solution as to how to forma-lize these “dysfunctional” requirements and include them in formal methods. INRIA will also contribute to the area of modeling and verifying the architecture of systems that meet processing requirements while experiencing faults or attacks. Current research into model-based engineering and model transformation techniques must be continued, focusing specifically on the difficult issue of testing. Finally, research into sound software veri-fication techniques for embedded critical functions on hardware circuits is needed for verifying hardware components and imple-menting secure hardware design flows.


Priorities


Life-Cycle, Supervision,

Diagnosis, Reconfiguration

and Maintenance

i Virtual Prototyping PlatformThe objective here is to develop a flexible, open, experimental research platform which will enable us to explore new design processes for embedded systems, provi-ding extensive possibilities for virtual prototyping, from the design phase for models of the physical object to the exe-cution architecture to be embedded. It is

expected to cover computational engineering technologies, synchronous and asynchronous languages, verification and validation tech-niques, code synthesis and the exploration of architecture design areas.

i Integrating Model- and Component-Based ApproachesThis challenge relates to developing a component-based architecture design method for critical embedded systems with difficult real-time constraints, that enables the integration of a model-based approach and a component-based approach for middleware and execution platforms.

Key Challenges

Supervision and diagnosis functions are designed based on the safety and reliability properties of all previous engineering stages, for example:• designing reliable systems, studying fault

trees and assessing failure risks;• closely studying the risk of failure propa-

gation according to operating modes, and combined reliability and functional design study;

• designing fault-tolerant architecture, with redundancy and voting protocols for super-vision during operation.

In addition, procedures must be developed for supervising the overall operating condi-tion of the artifact, identifying anomalies, diagnosing their sources and isolating faulty

hardware components. Intermittent faults and drift raise specific problems. Specific modeling for the needs of supervision and diagnosis must be applied starting with the initial design stage, in particular when the system is under-instrumented. Systems must be reconfigured after a diagnosed fault (for example by isolating a sensor or getting rid of a redundant element) in order for the main operation to continue, perhaps with lower performance, when main-tenance intervention is not possible (space systems) or can be postponed. Research problems in this area involve deve-loping non-nominal operating models and using them to meet supervision, diagnosis and reconfiguration requirements.


ComputationalSciences

3.2.2

�.2.2 Computational Sciences

Priorities


Biology, physics, chemistry, and other fields such as earth and environ-mental sciences, address increasingly complex processes combining the inte-raction of many different phenomena; each phenomenon need to be understood using specific approaches and mathematical representations. This complexity can be mastered by using several complementary analytical techniques in com-bination within a single, integrative approach. The possibilities for computatio-nal integration of multi-physical and multi-scale models, combined with rich measurement capabilities, multi-sensory data fusion and processing possibili-ties, and access to vast stores of data and powerful computation and visuali-zation codes, create very promising prospects for the development of scientific knowledge in most disciplines.In addition to the major scientific challenges of this area, there are also educa-tional, training and social issues at stake. Hopefully, massive access over the Web to simulation, real-life visualization and interaction tools will broaden the interest of many science lovers, make science popular again and encourage society as a whole to participate in culture and scientific debate.


Computational Material

From the nanoscopic scale to everyday objects and large structures, progress in the design of materials relies heavily on computational simulation. Material science has demonstrated the crucial role of the relationship between the microstructure and properties of materials. For example, refining the microstructure and/or reducing grain size is one way to optimize the properties of a material and adapt them to a specific function. Combining components within a composite material provides excep-tional physical and mechanical properties. Material mechanics has also developed micro-mechanical modeling tools to computationally simulate the behavior of materials according to descriptions of basic physical mechanisms (slip systems, phase transformation, etc.), thus improving our understanding of them. New materials can only be designed by taking into

account the complexity of these phenomena, and the way they interact and are superposed on various scales to produce different quali-tative effects on a macroscopic level. This applies, for example, to biocompatible mate-rials for medical use, adaptive materials (shape memory alloys) and piezoelectric ceramics. Lastly, modeling and computational simula-tion of the complex phenomena that occur during manufacturing processes (vibrations, instabilities, etc.) can be used to improve those processes.On the atomic level, new materials using metallic, ceramic, semi-conducting, supramo-lecular or polymer components are profoundly changing many technological sectors, from micro and nanosystems (MEMS, NEMS, NOEMS) to transportation, and from housing to healthcare and energy. In the field of energy,

This section describes some of the major areas in which ICST and INRIA can make an important contribution to the material, life and environmental sciences. These challenges are very diverse, ranging from atoms and molecules, cells and organs, up to indivi-duals, populations, biotopes and the entire planet. They relate to computational material, computational cells, computational plants, computational ecology, and the computa-tional biosphere and environment. Naturally, INRIA will work toward these interdisciplinary objectives in cooperation with expert labora-tories at universities and organizations such as the CNRS, INRA, INSERM, and CEA. The Institute’s objectives are ambitious in terms of computational integration, but they are clearly focused on applied mathematics and computer science, in particular in the following areas:• developing direct and inverse mathematical

models;• creating effective algorithms to respond to

the explosive growth of multi-scale model dimensions and effectively mapping these algorithms on intensive computing platforms, grids and suitable architectures;

• computationally integrating heterogeneous, differential, geometric, combinatorial and

stochastic mathematic representations within algorithms and software components;

• creating equipment and measurement tools for a broad range of phenomena, on a large scale if necessary, for example on compu-tational ecology sensor networks;

• processing and automatically interpreting data using multi-sensory fusion;

• combining models and data in real time, calibration, validation, classification of uncertainties;

• visualizing and manipulating predictions in a multimodal manner, designing and planning experiments, analyzing long term scenarios for change, and performing essential in-silico experiments, particularly when live experi-mentation is impossible or too complex.

INRIA’s ambition is to make significant contri-butions to these research topics, specifi-cally through its Modeling priority, which is strongly concerned. The two priorities of Communication and Interaction are also highly relevant, particularly for ubiquitous computing and visualization. The Institute aims to combine contributions produced within these priorities with multi-disciplinary research efforts involving partners in the material, life and environmental sciences.


Priorities


Computational Cells

Geometrical modeling of a nano structure material — GAMMA.

for example, new materials for photovoltaic cells and fuel cells are expected to produce substantial progress. Another example is the thin film and nitride, borate and lithium niobate crystals that can enable optical functions with a very high capacity for storing high-density information. Such progress raises many interdisciplinary questions, particularly in developing mode-ling and multi-scale computing techniques for nano-simulation materials – INRIA’s main priorities in the field. Complex materials require both micro-level analysis of atoms and of the basic chemical forces caused by interactions between electrons (governed by quantum models), and macro-level analysis of the mechanics of heterogeneous continuous environments. In addition to meshing, the entire field of modeling and simulation must be applied at the nanometric scale (the best-known objects on this scale are carbon nanowires and nanotubes). Simulation must be used as much as possible, both in studying and designing nano-components and in “assembling” them to produce usable devices. Simulation using physics and chemistry-based models can be used to assess the consequences of choices in terms of the electrical, magnetic, optical,

thermal and mechanical properties of the material. However, this approach raises many questions for ICST: data from very different measurement devices must be collated and the reliability and relevance of simulations assessed. In addition, when dealing with atoms, computing costs will be prohibitive unless dedicated algorithms can be developed for use on large computing grids able to interact with one another.

Up to now, bioinformatics has focused mainly on processing and mining systems for large data and knowledge bases and genome analysis. This field will continue to develop by substantially improving existing techni-ques (genome and metagenome sequencing) and continuing to develop new technologies (DNA chips, mass spectrometry, Chromatin ImmunoPrecipitation-on-Chip) that produce new types of data. These developments will expand the current role of bioinformatics in biological studies and their applications. Above all, they will create new prospects and improve the quality of genome knowledge. Eukaryotic genome sequencing will continue at an ever-faster rate in the coming years, like the recent developments in sequencing hundreds of bacteria and Archaea genomes. Comparative genomics will therefore continue

to grow in importance, giving rise to new approaches using new data, which will require new algorithm and computing methods and generate research topics, which fall within INRIA’s objectives.At the multicellular level, the aim is to esta-blish models accurately describing the exchanges of energy and signals used to coordinate cells, their motility, migrations, splits, differentiation and apoptosis, to turn these models into effective algorithms and integrate them. These scientific challenges involve key issues in medicine, pharma-cology, agronomy and animal production science.Cellular exchange must first be understood at the biochemical and molecular level. Myosin and other cell regulatory proteins that play a key role in these exchanges convert energy


Study of the interface of a complex from the immune system: a nano-peptide caught between two proteins.

chemically and mechanically through changes in molecular formation. Kinetic models rely on analyses of molecular structures from crystallographic imaging data, RMN and electronic microscopy. Structural algo-rithmic biology studies the links between structure, space and topology and macro-molecular function. It raises a large number of questions for computational geometry and motion planning, for example how to reconstruct and model the interface areas in biochemical contact to ascertain constraints and flexibility and to analyze admissible conformations, allowable relative motion and docking possibilities, which are essential to the functional expression of molecules.Genetics and functional genomics expand these structural biology models to protein gene expression mechanisms and the dynamic links within gene interaction networks. All of the proteins expressed at a given moment within a cell (the proteome) participate in a range of intracellular processes (inhibi-tion, regulation, amplification) and threshold phenomena, which are usually, viewed as non-linear dynamics. Epigenetic regulation mechanisms make these processes even more complex, requiring a systematic, inte-grative, biological approach to representa-tions and computing tools to be developed for use in describing the rules of basic interac-tions, as well as in modeling and simulating the global dynamics which these interactions may cause in cell cycles and in the cell’s responses to constraints and signals from its environment.Other types of modeling are needed to establish computational models of cells, for example models of cytoskeleton defor-mation, which allows a cell to move (moti-lity), cell migration mechanisms, intracellular exchanges and cell population dynamics. For example, the unstructured cell popula-tions in tumors and in regenerating tissues such as the liver and skin present a strong coupling of spatial architecture and func-tion. In the liver, the cells (hepatocytes) are structured in columns and layers to ensure optimal exchange of substances between the blood and hepatocytes. Data analysis and mathematical modeling methods on a wide variety of temporal-spatial scales are required to predict how intrinsic or extrinsic

changes on a molecular level (for example through drugs) affect the temporal-spatial processes of tissue regeneration. As has already been stated, we are not seeking to develop one single, generic cell model. Many types of models will be neces-sary depending on the types of cells studied and the applications for which these models are used. In pharmacological research, for example, predicting the effects of a molecule on a cell population will require models, which are suited to the physiological role of these cells and the genetic activity of the enzymes, their different metabolisms (energy, hormonal) and their ability to proliferate. One objective in terms of computational integration is to organize and formalize the vast and growing body of models, data and knowledge and develop effective combinations. This inte-gration should produce substantial advances in scientific knowledge and progress for agronomical, pharmaceutical, medical and veterinary technology. INRIA is already involved in several of the preceding ICST topics, combining dynamic and active intracellular imaging with geome-tric, combinatorial and graph algorithms, constraints, temporal logic and automatic control. The Institute wishes to redouble its efforts to improve understanding of the cell in cooperation with its partners in the life sciences.


Priorities


Computational Plants

INRIA’s expertise in modeling, computa-tional simulation and scientific computing is already recognized. The Institute is also an expert in meshing, particularly non-structured meshing. Through its work with physicists specializing in nanos-cience, it may contribute significantly to developing the “computational material” of the future.As bioinformatics and the life sciences expand in scope, several INRIA project-teams are working on studying the interac-tions between genes and their products in order to understand the regulatory mecha-

INRIA’s Position

nisms underlying the dynamic workings of cells. For example, modeling, simulation and analysis of gene regulation networks have been used to understand the response of various bacteria to nutritional stress caused by the network of interactions between its genes, proteins and small molecules. Mode-ling the cell cycle has led to optimization algorithms for therapy schedules that account for the circadian rhythm of the drug’s enzyme mechanisms, its genetic polymorphism, and descriptions of normal and tumoral growth of cell populations in homogeneous tissues. The main partners in the field are the Inserm,

CEA, the Institut Curie and the NIH. Plant growth modeling is being developed in partnership with Inra, CIRAD and IFN. Agricultural landscape simulation (one application of which is improved control of the use of GM crops), mode-ling and control of plankton growth in a chemostat and modeling microbial ecosystems leading to waste water depol-lution processes are just a few examples of the contributions to computational ecology made in partnership with Inra and Ifremer.

Simulation of tree growth— VIRTUAL PLANTS.

One fundamental problem for sustainable development is mastering the many causes of soil erosion, impoverishment and pollution from over farming and overuse of fertilizers and pesticides. Agricultural production needs can be met without compromising sustainable development if the needs of both plants and their environment are taken into account over the long term. This is the challenge of “computational plants”.INRIA’s objective is to develop and integrate growth models for plants and the many ways they interact with their environment. In the field of agronomics, this involves unders-tanding the mechanisms of organogenesis, photosynthesis, production and spread of biomass; soil water and mineral resources; atmospheric exchanges (light, humidity, temperature, wind, oxygen, carbonic gases) and the other physical constraints to which a plant is subject (mass breakdown, incline, etc.). The challenge for biological modeling is to analyze the genetic structures and develo-pment mechanisms of meristems. ICST topics affected by this research include applied mathematics, automatic control, computer graphics, geometry, combinatorics and of

course interdisciplinary links with botany, agronomy and genetics. Developing and integrating effective models on different levels, combining deterministic and stochastic components and enabling inverse problems to be solved effectively are key challenges. By meeting them, we should be able to progress from modeling an individual plant to modeling a plot of many different plants or species, or study the inte-ractions of plants with insect populations. ICST offers a way to expand computational plant models to cover seed selection, crop density optimization, control of fertilizer and pesticide input, and planning, environmental development and its visualization.In the field of computational plants, INRIA is also interested in modeling the growth of phytoplankton and controlling the growth of micro-algae. Some phytoplankton species are capable of absorbing carbonic gases and discharging them at the bottom of the ocean. Known models for these processes are incom-plete, fail to match observations and need to be reviewed, in particular for calcification, photosynthesis and warming mechanisms. Micro-algae offer a promising source of biofuel


Computational Ecology

Counting flamingos in aerial images — ARIANA.

production: if their biological processes can be properly modeled and understood, they should produce much higher yields than those from terrestrial plants. The Institute will work to develop complex microbial ecosystems for use in treating polluting substrates and

production energy. Research will focus on developing realistic models of interactions between species and substrates, producing biogases, and designing control strategies for effective depollution and optimization of energy production.

This is a particularly important interdiscipli-nary field at a time when the environment is changing rapidly and significantly. Input from ICST is crucial to computational ecology for integrating heterogeneous models and combining them with geographic informa-tion systems, geo-referenced data, sensor networks and environmental observation systems. The Institute aims to integrate animal popu-lation models at various trophic levels, for example differential models for insect or plankton populations, spatially structured models for reptile, fish or amphibian popu-lations, and individual models for species at higher trophic levels, such as birds of prey and large mammals. Each model describes the changes in a population according to its biotope, reproductive and feeding charac-teristics and its prey-predator relationships. Computational interactions between diverse populations (with one another and with the environment) can be used to study the responses of an ecological system to attacks from natural (fire, floods, etc.) or human (deforestation, farming, urban expansion) sources, and to develop effective conser-vation measures.Microbial ecology also raises issues relating to the density and distribution of microbial species, their competition and interactions with a substrate. Models of these systems are essential in designing control methods and techniques for treating waste and polluted water and depollution using an anaerobic process with optimal conversion of organic waste into energy.INRIA is involved in several complemen-tary areas of research that could relate to computational ecology, such as modeling

and computing, sensor networks, geogra-phic information systems and geographic visualization. The Institute wishes to apply some of this work to the interdisciplinary field of computational ecology.


Priorities


The Biosphere and the Computational

Environment

i Protein DockingThe objective here is to gain a better unders-tanding of the cooperative mechanisms of protein folding and docking by developing methods for analyzing biophysical data (crystallography, RMN) and simulation data (molecular dynamics). The challenge will be achieved if such developed methods are validated within experiments forecas-ting the structure of a protein complex from isolated partners (CAPRI experiment) and those forecasting the structure of a protein from its sequence (CASP experiment).

i Cell DynamicsWe wish to develop cell signaling reduced models for several important biological and medical applications. These models must include energy metabolism and physiolo-gical regulation (gene expression, protein status, any enzyme activity) within the cell

division cycle on the scale of a cell popula-tion, as well as physiological (hormones, growth factors) and pharmacological stimuli. Applications could include cancerology, for developing systemic biological models of metabolic cell networks and of disturbances to physiological control in tumoral cells.

i Plant Agrobiological ModelsPlants grow through a coordinated set of physical, molecular and cell processes whose complex interactions remain unclear. One objective in this area is building mechanistic models to better understand how the shape and identity of a leaf, flower or meristem can emerge from the integration of these mecha-nisms and how these are controlled by genes and/or the environment. Computer experi-mentation will be used to compare various hypotheses on the underlying mechanisms and support the models’ predictions with

experimental observations. The physio-logical model should also be useful in agronomical forecasts, depending on the environment, and crop management: this is one of the objectives of a source-sink model. Support through experimenta-tion on cultivated plants will be a further touchstone in this area. The work will be developed by studying typical plants such as arabidopsis and rice. This challenge has two components: modeling in order to better understand the biology of plant growth, with long term impact on selection and on varietal improvement, and predictive modeling of production, crop practices and the response of plants to climate variations (CO

2 levels in the atmosphere, tempera-

ture, precipitations).

Key Challenges

The biosphere is the part of the atmosphere, earth and oceans that supports life; studying it combines the two previous subject areas with climatology, geology and oceanography, and involves widely disparate scales. Much is at stake: the accumulation of greenhouse gases, global warming, changes in rainfall and distribution of fresh water, desertification of certain areas, rising sea levels and changes in coastlines, all of which affects the majority of the human population.The Institute intends to develop forecasting capabilities for use in designing and deploying strategies prevention and adaptation, which are critical in light of the inevitable changes underway. Computational environmental models will be used to analyze risk assessment scenarios for environmental policies or the lack thereof. Using demonstrative visualization capabilities, these models can also be used

in public awareness campaigns for preventive action over the long and even shorter term that demands significant investment as well as political and social commitment.Computational environmental models require solutions for observation, modeling, data assimilation, forecasting and monitoring over highly variable time frames (from real-time to very long term) with many interdependent processes. These can include geophysical flow, circulation, exchanges and matter and energy transformation. For instance, in atmos-pheric chemistry, complex gas kinetics, air mass movements and thermal exchanges are being studied in order to monitor local, regional and more global pollution. In hydro-logy, the conditions of water runoff and evaporation, soil absorption and erosion and the agronomical and ecological impact of developments (urban, hydrological, etc.)


Hydraulics of the Pearl river (China) — MOISE.

and catastrophes (spates) are modeled. In coastal oceanography, research into tides and currents is used to study pollution and shore-line development. In general, studying the interactions between ocean and atmosphere is vital to understanding ocean circulation and its climatic and ecological impact. Physical and biological environmental models must also be merged, for example the biological phytoplankton models mentioned previously in the field of oceanography.In this vast field of research, INRIA and its partners will focus specifically on the following ICST-related issues:• observation, using fixed or mobile sensor networks (balloons, floating probes), satel-

lite imaging and geo-referenced data. Data acquisition requires solutions for representa-tion and adequate algorithms for identifying and monitoring the movements of interesting phenomena, which can be applied to early detection of disasters. It also requires an effort to optimize the observation system; • modeling, and more specifically combining heterogeneous representations, assimilating incomplete, imprecise and uncertain data, and qualifying models (see �.1.1);• early detection, monitoring rapid phenomena and slow drifts, improving diagnosis;• in-silico experimentation, assistance in plan-ning and environmental risk management;• viewing long term environmental changes.


Priorities



ComputationalMedicine

3.2.3

�.2.� Computational Medicine

Priorities


The field of medicine and human biology offers many scientific and technological challenges. It covers significant health-related social issues, which also have major economic implications. INRIA’s stated scientific ambition in the field is to contribute to the transition from knowledge expressed as collections of cases, describing the highly complex reality of living beings, to mathematical models explaining and forecasting the mechanisms involved in a given biomedical process. This priority focuses on a multi-disciplinary contribution to biomedical observation, modeling and simula-tion at all levels, leading to a better understanding of human biology and also to diagnosis, design, implementation and optimization of new therapies. The Institute intends to focus specifically on a few important categories of pathology, including cancer, cardiovascular diseases and neurodegenerative and nervous system diseases.This priority is the natural extension of the preceding ones, in particular mode-ling, interaction and computational sciences. There is a continuum between the biology issues presented here, which focus on human biology, and those presented as part of the previous priority, which cover other aspects of animal and plant biology and bioinformatics. Other promising links between medical technology and computational engineering can also be seen, for example in the development of systems to assist and compensate for motor or sensory impair-ments (prostheses, neuroprostheses).


Over twenty INRIA project-teams are focusing on this priority. Another twenty project-teams are working on related sub-jects relevant to this field, from meshing, modeling, probability and geometry issues to learning and robotics. Nationwide col-laborative research work is underway for the objectives described here. The Institute is drawing on a long tradition of research and strong, internationally recognized skills in modeling and scientific computing as well as in vision and image processing. A great deal of software is available to support INRIA’s work on this topic, and several software packages have been used in industrial applications, generally through spin-offs.

Naturally, INRIA relies on national and inter-national partnerships, which are essential in this multi-disciplinary field. Within France, its main relationships are with Inserm, Inra, CEA-DSV (as part of the Neurospin plat-form), the Institut Pasteur, Institut Curie, hospital departments and the CNRS. INRIA is a member of the Institute of Complex Systems scientific interest group, and a founder of the Rhone-Alps Infectiology Therapeutic Inno-vations RTRA advanced research network. Collaboration within these institutions, for which it provides modeling and computing support, will be relevant for this topic. In addition, the Institute has several industrial partnerships, which will be developed as part of this priority.

At the European level, INRIA has many academic connections, for example with Guy’s Hospital in London, the Swiss Insti-tute of Bioinformatics and the Weizmann Institute. These relationships will no doubt be consolidated as part of the work on the Virtual Physiological Human described in the 7th FP. On an international level, the Institute is developing a close working relationship with the NIH, in particular with its National Institute of Biomedical Imaging and Bioengineering.

INRIA’s Position

Simulation of heart dynamics — MACS.

This priority has two aims combining science and technology:• tightly coupling the observation, modeling

and assimilation of biological data to create a thorough description and accurate measu-rements of living beings by developing and using new biological, medical and multi-sensory fusion imaging and observation methods. The models designed must be just as complex as the observations they cover if the models are to be reversed for data assimilation, and their precision and properties correctly qualified;

• combining biology and medicine. These precise, personalized, clinically qualified biological models will be used to develop medical and pharmacological technolo-gies for predicting change, detecting and diagnosing conditions, stimulating physical and biochemical actions and measuring their effects, commanding prostheses, planning, optimizing and providing assis-tance for therapy protocols and surgical interventions.

INRIA’s scientific and technological ambitions cover a broad range of multi-disciplinary topics requiring expertise in applied mathematics, signal and image processing, automatic control and computer science. The Institute’s research scientists, in partnership with biologists, doctors, chemists and physicists, will speci-fically address problems relating to imaging, modeling, computing and simulations, at the molecular, cellular, anatomic, functional and physiological levels.In biological and medical imaging, the Institute will work to improve control of the various means of in-vivo data acquisition: intracellular imaging, confocal microscopy, optical imaging, anatomic and functional magnetic resonance imaging, magneto-ence-phalography, x-ray tomodensitometry and positron emission tomography. This involves developing complete algorithms for processing and interpreting images and signals stem-ming from the use of these various methods, and then merging them with one another or with complementary biomedical signals (ECG,


Priorities


Modeling of the brain activity — ODYSSEE.

EEG, flow and pressure measurements, etc.). The objective is to acquire anatomical and functional data with the best possible spatial and temporal resolutions. This increasingly complex data cannot continue to be interpreted using visual means alone. A quantitative and possibly stochastic interpretation may help to manage the acquisition and measurement processes; it may be combined with diagnostic aid and therapy processes. Intracellular and tissue imaging may be used to identify cellular and intercellular signaling paths used in the molecule metabolism, both endogenous and exogenous, and in cell proliferation, and thus to develop and validate the models needed to understand living beings and design and optimize new therapies.Modeling and biomedical data assimila-tion will focus on processes in cells, organs, complex functions (for example cardiovas-cular or locomotive functions) and organisms. They will include both anatomical (structural) and physiological (functional) representa-tions and heterogeneous data. For example, a cardiovascular system model may include combined geometrical, biomechanical and bioelectrical representations with fluid dyna-mics and cardiac muscle perfusion. Solving inverse problems for such models using estimation, learning and optimization techniques is very difficult in terms of algo-rithms. Data assimilation leads naturally to a close association between modeling problems and data acquisition, processing and inter-pretation problems. The depth of the models required to understand a highly complex biolo-gical situation will be limited by the wealth of data available. The resulting compromises will depend on the application of the model, most likely leading to each specific organ or function having its own type of model. For an appli-cation in therapy optimization, for example, a model must represent the expected effects of a combination of therapies (drug synergy) and the toxic effects on healthy tissue. This requires detailed observation of cell physiology well beyond the growth or mortality rate.Developing such models raises problems for computing, simulation, optimization, visuali-zation and uncertainty measurement (listed in section �.1.1) and more generally for qualifying models, which is essential for medical applica-tions. In the context of this topic, computational

analysis, geometric and probabilistic compu-ting techniques are closely tied to biology, chemistry and physics. The ambition to combine biology and medicine requires customized models, which in turn demands the development of computational anatomy and computational physiology. The former uses anatomical statistics to determine the normal variations between individuals for a given organ, clearly distinguish these varia-tions from pathological deviations, and detect such deviations in medical images and data. In the latter, customized physiological models would be used to explain and predict functional properties, explore the incidence of physical conditions and perfect therapies. For example, in cancerology, pharmaceutical genetic studies using DNA chips could be used to prescribe customized chemotherapy.For medical technologies, INRIA’s ambition is to build on its algorithmic research into imaging and modeling to help develop techniques for prevention, detection and quantitative diagnosis, forecasting changes, simulation, regulation and optimization of therapies. Several of these objectives are inseparably linked to one another. Others require comple-mentary research, for example into the appli-cation of virtual reality to therapy, into surgical robotics and enhanced reality for simulation, and into intervention assistance for radiation therapy and non-invasive surgery, guided by comparing images and models. Another example of the link between measurement and action involves quantifying the mecha-nical characteristics of muscles in the case of motor deficiency to provide patients with optimized stimulation.Finally, it should be stressed that this research must be carried out in close cooperation with biologists and doctors, particularly when essential experimental components are concerned. This field raises questions of ethics and best practices, which INRIA will monitor during dialogue with user associations and elsewhere.


i Modeling, Viewing and Interactively Manipulating a Computational HeartThe goal here is to develop personali-zed models of the human cardiovascular system that include all of the processes of electrophysics, electromechanics, blood flow dynamics, arterial circulation, per-fusion and cardiac muscle biomechanics. The Institute aims at developing imaging and instrumentation techniques needed to elaborate and qualify these models. This challenge includes building an interactive platform for biologists and doctors to view cardiovascular phenomena. The platform should be able to explore a personalized computational heart using a multimodal, visual and haptic interface and implement diagnostic and therapy simulation software tools. Its purpose is to address clinical pro-blems and contribute to improving medical devices. Close cooperation between INRIA researchers and biologists and doctors will be the key to this milestone.

i Computational and Functional Brain MappingThis challenge consists in developing perso-nalized anatomical and physiological models of the human brain, combining various types of functional brain imaging techniques and including them into maps locating the neuronal fibers and cortex activity. These models would highlight the link between the spatial structure of the maps and their function, and analyze observed variability according to genetic and behavioral infor-mation. Eventually, these models would be developed further for clinical technologies,

enabling surgery guided by overlaying images and models. In general, understanding multis-cale interactions between neuron populations in the human brain requires INRIA and its partners to develop and share mathematical modeling and simulation tools, and to build and implement neurobiological measurement databases. Better understanding these pheno-mena will move us substantially closer to the necessary synergy between neurosciences, com-puter science and mathematical modeling, pro-viding neuroscience specialists with methods for assessing the computational properties of their phenomenological models.

i The Interface Between the Nervous System and Artificial SystemsThis challenge involves using anatomical and functional models to compensate for a motor or sensory impairment by activating the rele-vant central nervous or peripheral structures (neuroprostheses).Just as a pacemaker can trigger a contraction of the myocardia, it is possible to restore motor functions by stimulating the motor nerves, and the same applies to sensory functions (such as hearing, with cochlear implants which stimulate the cochlea). These therapy approaches have a common base in technology and electrophysical research, but must be adapted to each applica-tion. It is now possible to contemplate resto-ring very complex functions such as standing upright in balance, certain sensory functions, and to modulate the central nervous system in the case of diseases such as Parkinsons and epilepsy. However, accurately controlling forms of sensory and motor replacement requires new measurements and models of the relevant

nervous system structures. The implants of the future will be capable not only of activation, but also internal, and therefore highly accurate, observation of the periphe-ral or central nervous system, broadening fields of diagnostic and therapy application which are currently limited.

i The Computational Surgery EnvironmentThe aim here is to develop and experimen-tally implement visualization, planning, enhanced reality and robotics capabilities to help with interventions such as heart and/or brain surgery, using the models and methods developed in the two previous challenges.

i Medical Model Simulation and Integration Software PlatformThis challenge involves developing a robust software kernel in which the different models and components of a simula-tion can co-exist, such as rendering and collision models, deformable, haptic, physiological models, together with the management of relationships between the different representations of the same organ. In addition to the kernel, there will be a set of modules and software libraries providing different functions: collision detection algorithms, deformable models, realistic photo rendering methods, optimal management of computing resources, parallelization, computational solvers and management of interactions between heterogeneous objects within the same simulation.

Key Challenges


Priorities


3.3Social Concerns Covered

by INRIA Priorities

The reasons for which the Institute has chosen the seven priorities have already been given and explained in the previous sections with respect to social issues and economic stakes. At this point it is worth returning briefly to the main social motivations behind INRIA’s priorities, particularly those that concern several priorities.Environment and related issues fall into the categories of modeling and interaction. The stated objectives for computational ecology, the biosphere and the computational environment explicitly address several envi-ronmental challenges. Sustainable development is mainly present in the areas of computational plants and computational ecology. Health is a priority in its own right, through computational medicine. Other priorities also address health challenges, e.g., in Interaction, or Computational Sciences. Demographics and the issues raised by an aging population are partially covered under the priorities of Interaction, Communication and Medicine.Energy will be the subject of research efforts for modeling, controlling and optimizing the use of traditional sources of energy and for developing new sources, such as solar power, biofuels and thermonuclear fusion within the ITER federation.Transportation is covered mainly under Computational Engineering, since embedded systems play an increasingly important role in this field, and within the Interaction priority. Services for people and the development of the information society are dealt with mainly in the Commu-nication and Interaction priorities. Training and education are covered in the Interaction priority, particularly through visualization and virtual reality. These challenges raise problems that are also present in the semantic and service Web and in the Communication priority.Security raises problems dealt with in the Programming, Communication, Interaction and Computational Engineering priorities. The Institute’s efforts in this interdisciplinary field will be coordinated specifically within the Scientific Interest Group dedicated to the surveillance, safety and security of large systems.


�.� Social Concerns Covered by INRIA Priorities

Priorities


3.43.4Emerging Fields

The Institute’s seven strategic priorities raise important fundamental problems, which are unresolved and have major scientific and technological implications. INRIA’s research resources are mainly devoted to address these priorities. However, INRIA wishes to remain open to emerging themes in clearly formalized scientific fields.In order to encourage the emergence of new scientific fields, INRIA is gathering the appropriate resources to carry out “exploratory operations.” The research supported by these resources is very long-term and high-risk. It should serve as an incubator for brand new research ideas to be explored by both experienced and junior research scien-tists. As in ERC’s case, the fundamental criteria will be creativity, originality and excellence for conducting advanced research that clearly departs from the traditional disciplines. INRIA intends to encourage highly exploratory work.Examples of exploratory research areas include:• new forms and means of processing information. The fundamental characteristics of matter (quantum behavior,

atom dynamics, cells, etc.) can be used to develop radically new types of logic and components; • new computing methods and new algorithmic paradigms inspired by nature, biology and chemistry. Current

models (based on the Von Neumann model) are reaching their limits, and other models will soon be necessary;• new modeling and simulation paradigms;• new approaches for building reliable, safe and highly available information systems (durable over several centuries);• pervasive computing based on highly dynamic architectures containing a potentially large number of components

of sometimes-uncertain behavior, with paradigms to facilitate the emergence of significant properties;• new approaches to programming, for example using imitation;• representation, model and data integration techniques over a very broad spectrum, capable for example of easily

establishing the environmental effects and energy consumption of any product (end-to-end life cycle);• new capabilities for user interfaces. This recurrent subject deserves as much attention as can be spared. New

methods such as 3D spatial interaction must be studied to provide robust support to other, older methods such as speech.

New directions for interdisciplinary research, particularly in the human and social sciences, can also provide avenues for exploratory operations. For example, modeling techniques for the “computational human” are relevant to socio-logy. ICST is also useful to the legal sciences for the formalization and semantic use of legal texts as well as liability, legal protection, and even software and systems ethics.INRIA will seek out new prospective research both internally and with its partners; it will remain very attentive and open to the emergence of new research areas and encourage risk-taking that may lead to potential scientific breakthroughs.

Actions

Inthischapter:

Actions and Strategy for Achieving the Objectives

4.1 INRIA’sRoleinFrance page98

4.2 ImprovingtheInstitute’sAttractiveness page100

4.3 Research,DevelopmentandTransfer page110

4.3.1 OrganizingResearch page110

4.3.2 TechnologyDevelopment page110

4.3.3 TechnologyTransferandInnovation page112

4.3.4 TrainingthroughResearch page114

4.3.5 DistributingScientificInformation

andKnowledge page115

4.3.6 EvaluatingResearchandTechnologyTransfer page117

4.4 EuropeanandInternationalRelations page118

4.4.1 INRIA’sCommitmentinEurope page118

4.4.2 CooperationwithAsia,NorthAmerica

andSouthernCountries page119

4.5 InternalOrganizationandOperation page120

4.5.1 HumanResourcesPolicy page121

4.5.2 InternalOperations page122

Actions


INRIA’s Role in France

4.1. The general organization of research in France, which is built around the same institutions created in the 1950s to 1980s, has recently been experiencing accele-rated growth with the creation of the ANR and competitiveness clusters, the crea-tion of PRES’s and RTRA’s, the research program law and the law on the freedom and responsibility of universities (see 2.�.�). This change is a response to the incredible pressure of globalization in research and innovation work and its role as a driving force behind social and economic development and world competition. In particular, it aims to strengthen the position of universities as regional research and training operators, making them world leaders.INRIA has to play an important role within this national policy to strengthen university sites and form world-class teaching and research clusters. It is responsible for defining and carrying out established scientific policy in high-priority fields. Several countries have begun structuring their scientific policy, in particular in ICST, around national opera-tors. Several examples include Max Planck Gesellshaft and Fraunhofer Gesellshaft in Germany, which are foundations receiving most of their funding from the government. In Holland, the CWI, whose scope of activity is similar to that of INRIA, is part of the NWO, a government body. In the United States, most of the large government departments fund and directly or indirectly manage national research organizations such as the NIST Laboratories, NIH Institutes and Centers and National Centers administered by the Battelle Group. In Australia, the NICTA research center is funded by the govern-ment and various Australian ICST bodies. In Japan, the National Institute of Advanced Industrial Science and Technology plays a leading role for national scientific policy in its fields. While the organizations mentioned in these examples all have specific charac-teristics and distinct organizational models, in all cases these centers organize global research strategies and team up the univer-sities they support.Given the specific nature of the information science and technology field, the changes already underway in France must go along with a stronger INRIA, the national organi-

zation focused in ICST who is able to:• work with universities to motivate the best

teams in France – those with high visibility and a reputation for scientific excellence – and provide attractive training through research;

• develop a national scientific strategy based on a European and international pers-pective, and focus most of its projects proactively around this strategy;

• implement a development, technology transfer, innovation and spin-off policy through partnerships with the main indus-trial players in the field.

ICST is a young field experiencing pheno-menal growth, which from the outset has been global and competitive in nature, relying more on intelligence than previously acquired technological assets or major infrastructure (apart from the Internet). INRIA has carved out a niche and developed an organizational structure, which is perfectly suited to current conditions. This organi-zation, structured around highly mobile people rather than strict, compartmentalized structures, is one of the essential factors in the Institute’s success.INRIA is an organization which is fully dedi-cated to a high-priority scientific domain and whose mission is to develop a consistent nationwide scientific and technology transfer policy, in keeping with European policy. In a field which is growing rapidly and diffi-cult to predict, and which is essential for economic, social and cultural development, it is crucial to analyze impacts and strengths before defining a research strategy, making choices and adopting a dynamic, proactive organization. This is why INRIA considers itself to be an essential link between the research funding agencies (ANR, European Commission, ERC) and regional university teaching and research clusters. To this end, the Institute reaffirms the four basic tenets of its work in favor of research, development and tech-nology transfer in ICST:• close-knit teams working on a focused,

high-level scientific project. To maximize the impact of its work, the Institute initially chose a horizontal structure with little hierarchy, entrusting its scientific policy largely to project-teams under scientific

4.1 INRIA’s Role in France

Actions


leaders with ambitious, competitive and highly focused projects. These autono-mous project-teams, which exist for a limited amount of time, are assessed natio-nally according to a procedure, which emphasizes international positioning. The Institute is convinced that these research project-teams are an essential element of its success.

• dynamic partnerships. INRIA is acti-vely involved in partnerships with French universities and research organizations located on its geographical sites. Today, over 80% of INRIA’s project-teams are joint undertakings with partner establis-hments. By building these joint teams of international-level researchers who believe in INRIA’s strategy, the establishments build entities with sufficient critical mass. The Institute is committed to working with partners willing to provide resources, parti-cularly human resources, to support the project-team and its work. Cooperation is established in a climate of trust and transparency, based on sharing results and revenue in proportion to the resources allocated and sharing efforts to maximize efficiency;

• project-teams involved in producing knowledge and technology. Scientific research produces both knowledge and technology. The relationship between knowledge and development meets social expectations as well as scientific require-ments. To a greater or lesser extent depen-ding on the precise field, ICST involves an experimental aspect, and research uses and often develops technological and software platforms. Project-teams generally adopt a scientific procedure that produces both knowledge and tech-nological development, and its results are assessed based on both of these components;

• project teams committed to technology transfer. The government has entrusted INRIA with a special mission in promo-ting ICST. By placing the Institute under the Ministry of Industry, the government has demonstrated its political desire for the Institute to transfer technology in partnership with all socio-economic

sectors. INRIA has worked for over 25 years to perfect a highly effective model for facilitating technology transfer and start-up companies, based on a high-quality, decentralized, coordinated, profes-sional internal structure. The Institute has demonstrated its ability to complete its mission by signing a series of stra-tegic agreements with major companies and joint teams with industrial partners, performing research and development work, creating start-ups and developing a clear policy on distributing software and defining standards.

The boxes in this chapter define in detail the way these tenets are applied by the Institute’s eight research centers for all research, development, technology transfer and partnership tasks. Each center must adopt specific agreements with its regional partners specifying the details of joint support for research operations within joint INRIA project-teams, and then design and implement a dynamic scientific policy.The cornerstones of this organization are assessment and recruitment. An assess-ment must be performed before any decision affecting the future of a project-team can be made. This strict assessment is performed by independent academic and industrial experts from France and abroad, chosen for their competence and impartiality; it takes place every four years for all project-teams working on the same topic nationally. The experts’ recommendations are taken very seriously. They decide the future of project-teams in each discipline (whether they should be expanded, continued or shut down) and also provide a better unders-tanding of INRIA’s international position in each discipline and any improvements that must be made.In such a rapidly growing organization with a very dynamic structure, the value of individuals is paramount. The Institute aims to attract the best people for every position type and level. It does this using a variety of employment categories – both permanent and fixed-term positions – that take advantage of legislation. Having a variety of employment categories provides some flexibility in terms of salaries. INRIA’s

INRIA considers itself to be an essential link between the research funding agencies (ANR, European Commission, ERC) and regional university teaching and research clusters..


Improving the Institute’s

Attractiveness

4.2The field of ICST is characterized by fierce international competition in which productivity and scientific quality rely not on substantial capital investments but rather on research scientists themselves. Because of this, a fundamental objective for research in France is improving its attractiveness on an inter-national level. INRIA’s influence and attrac-tiveness within the international scientific community are and will remain major criteria for its success and ability to energize national research. It is clear that the Institute cannot attract new researchers solely based on the reputation of excellence that it has developed, although that is certainly an essential factor that must be protected. Instead, it must expand its human resources, communications and international policy. Increasing INRIA’s capacity for hosting and recruiting foreign researchers and students will remain a major priority for the coming years. The policy for recruiting permanent research staff aims to maintain a proportion of roughly one-third foreign scientists, by advertising positions even more widely and emphasizing the Institute’s image and presence on the international scientific market for ICST. For students, INRIA will expand its internship program for hosting Masters-level interns from foreign universities, as well as its CORDI-S program, begun in 200�, which is specifically directed at young (French or foreign) PhD students wishing to do their thesis at a univer-sity or school far from the one in which they did their Masters, and prioritizes candidates who have studied abroad. The Institute is committed to working with French engineering schools and universities to provide bilingual

French-English Masters courses, enabling non French-speaking students to come to France. This opening for students with foreign diplomas will also be available through the postdoctoral hosting program.Facilitating scientific cooperation with leading international teams as well as mobility for researchers is very effective in improving attractiveness. Programs developed and implemented over the past several years will be continued and expanded, including associate teams (promoting cooperation with foreign universities by providing financial support for exchanges and joint workshops), sabbaticals (long stays for researchers) and explorers (short assignments for researchers, post-doctoral and PhD students). Mobility of scientists within universities and companies increased considerably in recent years, but it has just begun to slow down. The Institute will take advantage of existing and future regula-tory provisions, as well as the economically dynamic ICST sector itself, to boost mobility through incentives and assistance measures; with the agreement of its governing authori-ties, it is prepared to develop experimental programs in this area. The results of INRIA’s hosting policy over the last eight years have been very posi-tive, in terms of promoting openness among the Institute’s teams and producing results for the scientists and engineers who have participated. The ambition for the next few years is to expand it even further, to hosting university professors and senior scientific civil servants on assignment for specific projects, providing “associate engineer” contracts for young graduates and employing industrial and academic specialists on a short-term

4.2 Improving the Institute’s Attractiveness

recruitment policy is extremely open to international applicants, particularly for scientific positions; in fact, the number of foreign researchers has been steadily growing since 2000. Fostering the right conditions for high-level recruitment is a priority for INRIA’s management.

The future of ICST in France will depend on INRIA and its partners’ capacity to build upon and develop this operational model, ensuring that it remains attractive and relevant on an inter-national level, and above all constantly seeking young research scientists worldwide who will be the scientific leaders of the future.

Actions


INRIA’s influence and attractiveness within the international scientific community are and will remain major criteria for its success and ability to energize national research.

basis. The Institute will attempt to make its permanent positions more attractive not only through its basic tenets – the dynamic nature of the teams, interaction with the economic world, good working conditions, flexible organization and effective research support – but also through support for career plans and improved salaries and benefits. With the Research Treaty, some measures have been discussed and others already implemented, such as changes to the rules for promotion and provisions for “remuneration for public-interest positions,” which provide assistance for taking on positions of responsibility. If necessary, INRIA is willing to experiment in this area as well.The Institute must make a concerted effort to appear more attractive in all of its external communications, well beyond information about the institution and its assets. Although research into computer science and applied mathematics are the basis for the current transformations in society, the general public is still largely unaware of this fact. This lack of knowledge, and occa-sionally mistrust, by people in general is a problem for scientific research, especially for computer science and automatic control, which are commonly perceived as “tools” rather than scientific disciplines, whether they are seen as promising or threatening. This perspective is of particular concern among young people, who have begun to abandon scientific study in increasing numbers. The Institute must correct this incorrect image: scientists are responsible for opening the “black box” and demonstrating the educational value of their research in this field to a wide audience.This is why INRIA will be directing its external communications mainly at the non-scien-tific public, including young people, to help remedy their lack of knowledge about computer science research. A special effort will be made to increase the media presence of the Institute and its researchers, to provide more general scientific presentations on INRIA’s website and to organize events dedicated to ICST research. In order to reach young people effectively, over the next 4 years the Institute will also be promoting scientific culture in secondary schools (see 4.�.5). Additional effort will focus on informing French and European decision-makers about research results and technology transfer work.


The Scientific Specializations of

INRIA Research Centers

The eight INRIA research centers, which are briefly described in Section 1 (see 1.3), apply the Institute’s strategic orientations as shown in the boxes on the following pages.

INRIABordeaux–SudOuestResearchCenter INRIA Bordeaux – Sud Ouest Research Center’s skills will be used to support topics studied by the Aerospace Valley competi-tiveness cluster; INRIA intends to plan its growth in Bordeaux according to the develo-pment of this cluster. Industrial and academic partnerships will also be a determining factor; these include Total, Safran/Turbomeca, Thales, Rhodia, the CEA (for the Laser Mégajoule research program), France Telecom, EDF, Airbus and the SNCF, both directly and as part of the Aerospace Valley cluster. The center’s development capacity and its committed partnerships suggest growth will attain at least 50% over the next 4 years. The center’s main priorities, which benefit from world-class expertise available in the region as well as substantial external contributions, are as follows:

Modeling, computing and parallel systems MODELING – COMPUTATIONAL SCIENCESLife-size simulation of complex physical, chemical, geological, biological and medical systems relies on concepts and techniques drawn from computer science and mathema-tics. These methodological developments, conducted in close cooperation with applica-tion sectors within industry, are highly inter-disciplinary and rely on optimized adaptations for the effective use of high-performance computing platforms. More faithful, interac-tive and rapid modeling will be possible by

constructively meeting algorithm development challenges and studying and implementing sequential and parallel systems allowing for virtualization. Models for the behavior of autonomous machines interacting with their environment will also be developed in cooperation with local cognitive and robotics research partners.

Simulation and visualization INTERACTINGViewing multi-scale exogenous or simulated information requires research into algorithmic, graphical and audio representation (which depends on the rendering context, ranging from mobile phones to advanced �D virtual reality devices). These methods, combined with scientific simulations in pilot environments, lead to chains of interactive processing serving as the initial building blocks for computational platforms developed by the Institute’s industrial partners. Fundamental problems include data representation and transfer.

Formal systems PROGRAMMINGFormal systems are at the center of several teams’ research projects, in terms of both deduction and semantics in natural language for computational linguistics, and of programming environments involving proofs and programs. Research efforts are focusing on first- and higher-order linear logics and deduction and related proof mechanisms. Specific concerns involve the modularity and orchestration of basic components for programming systems, and proof in situations requiring reliability and security.


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INRIAGrenoble-Rhône-AlpesResearchCenter INRIA Grenoble - Rhône-Alpes Research Center is committed to building on the three major scientific subjects that require conti-nued investment to achieve the best possible results, while participating in the strong regional dynamic present in the area’s world-class competitiveness clusters. These include micro and nanotechnology development on the Grenoble site, which relies heavily on software components, and biology and health modeling on the Lyon site. In Lyon, the Center’s teams take part in the “infectiology innovations” topical advanced research network. The center’s three major priorities are as follows:

Mastering dynamic and heterogeneous resources: embedded systems in computing and communication infrastructures COMMUNICATING – COMPUTATIONAL ENGINEERINGAs the traditional model of a fixed program running on a well-defined architecture has become outdated, the design and use of systems using software have experienced radical change. Software deployment environments now range from embedded systems-on-a-chip to computing grids and even self-organized networks, and are highly specific, dynamic and heterogeneous. In order to design reliable software geared to the requirements of communicating microsys-tems, researchers must consider hardware-software interfaces and architectures and apply advanced compilation and verification techniques. Algorithms and scheduling for the purpose of optimizing computing infras-

tructures are essential to the development of distributed systems, peer-to-peer architec-tures and sensor networks.

Modeling and simulating multi-scale and multi-component phenomena MODELING – COMPUTATIONAL SCIENCESMany phenomena, both natural (from geophy-sics to life sciences) and artificial (light effects, robotic system movement), are multi-scale (occurring on several scales in space and time) and multi-component (involving the interaction of several partners). Providing explanations for them, producing virtual instances of them, modeling and simulating them all raise common questions in terms of algorithms and digital technologies. The computer science subjects involve a broad activity range from data representation and assimilation to probabilistic modeling and the study of dynamic systems. One key challenge is combining individual models to explain the complexity of the phenomena involved. Finally, an important characteristic of this area is that interdisciplinary collaboration is required in each of its fields of application (physics, biology, medicine, etc.).

Perceiving and interacting with real and virtual environments INTERACTING Developing tools to serve human activity involves mastering data acquisition and processing (understanding, classification and ordering) and their impact on the outside environment. Understanding the processes of multi-sensory perception and cognition increases interaction capacity in both direc-tions, between users or automated systems and real and virtual environments.


INRIALille-NordEuropeResearchCenter INRIA Lille – Nord Europe Research Center will expand to reflect the Institute’s partnership policy within the Haute Borne science park, which will be the geographical center for this development. Joint project-teams will be created with other establishments in the region and neighboring European universities, and 50% growth is projected over the next five years. The competitiveness clusters (I-Trans for land-based transportation and particularly the Trade Industries cluster) and the research

campus for interdisciplinary research and technological innovation studying ambient

intelligence under the supervision of the CPER will together offer a golden

opportunity for scientific deve-lopment and partnership with

businesses. The Center’s scien-

tific priorities are as follows:

Software infrastructures for ambient intelligence COMMUNICATINGAn important issue for the Center is transpa-rent, adaptable and easy-to-deploy ambient systems. These systems will interact with people in a variety of increasingly natural ways through widely distributed sensors. The Center’s scientific objectives include solving the problems of self-organization, coope-ration with a large number of ambient and personal devices and working with limited resources (energy, memory, low cost) based on a combined hardware/software design approach. These systems must be reliable, forward compatible and interoperable, requiring progress in the fields of formal measurement, operating systems and middleware. Service applications will be given priority, particularly within the Trade Industries cluster.

Modeling and interaction with living systems COMPUTATIONAL SCIENCES – COMPUTATIONAL MEDICINE The multi-scale and multi-model approach to virtual and enhanced reality will be used to develop increasingly realistic platforms for medical simulation. Work with biologists, both for regulation networks and comparative gene-tics, will combine bioinformatics algorithms and computational methods such as symbolic and statistical computing.

Modeling and simulation MODELINGThe Center’s objectives in this area include solving problems relating to the environ-ment and electromagnetism. Discrete and continuous generic modeling techniques will be developed, in addition to learning, identification and control techniques using algebraic methods.


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INRIANancy–GrandEstResearchCenter INRIA Nancy – Grand Est Research Center is working to finalize its efforts with partner universities in the Nancy cluster to make orga-nizational changes facilitating the development of ICST research in keeping with the scientific policies of the various establishments. The Lorraine institute’s main strength is in compu-ting research, which it will continue to develop, but it also wishes to move into applied mathe-matics, automatic control and interdisciplinary topics combining ICST and other scientific sectors, in particular the life sciences and the human and social sciences. The Center hopes to expand its influence throughout the region, particularly in Strasbourg, Metz and Besançon; in the medium term it intends to create cross-border joint project-teams. All of these avenues of growth will ensure high-level, international scientific excellence and the development of priority research. INRIA Nancy – Grand Est Research Center will prioritize the development of three areas of activity:

Cognition: Perception, language and knowledge INTERACTINGThe Nancy center has earned international recognition for its work in modeling and computational analysis of the cognitive capacities that make us human - our ability to perceive, reason, communicate and use information. Research focuses on automatic language processing, speech processing, extracting semantic information from large multimedia databases, autonomous robotics, statistical model-based learning, enhanced reality, collaborative work and developing computational models in an immersive or interactive setting.

Simulation, optimization and control of complex systems MODELING – COMPUTATIONAL SCIENCESThe complexity and size of real systems to be modeled, simulated or controlled offer significant scientific challenges. Meeting these challenges demands high levels of expertise combined with intensive compu-ting methods and computer science, and mathematical theory for control and opti-mization. In this area, the Center aims to develop methods and tools for use in the identification, control and optimization of systems combining different large-scale dynamics (both continuous and discrete, and of finite and infinite dimensions). Research will focus on systems from plasma physics (ITER project), rapid computational methods for graphic computing, scientific visualization and the design and control of autonomous robots, particularly for biomimetics.

Computing systems security and reliability PROGRAMMING – COMPUTATIONAL ENGINEERINGThe reliability and security of software integra-tion systems play a vital role in the adoption of those systems in an economic, legal and social setting. They may be software, hard-ware or hybrid systems, such as embedded systems or computing infrastructure. Research focuses on the reliable design and certifica-tion of software and protocols, verification of correct operation and guarantees with respect to the use of resources; the neces-sary performances for an acceptable level of services; computer security; and prevention, detection and protection techniques guarding against attacks on networks and distributed services.


INRIAParis–RocquencourtResearchCenter Today, INRIA Paris – Rocquencourt Research Center is a major player in research in the Paris region. The Center is actively involved in the CapDigital, Mov’eo and System@tic competi-tiveness clusters and in the Digiteo and Paris Mathematical Sciences advanced research networks (RTRA’ s). Much of this joint work is

carried out in close cooperation with the other INRIA Research Center in metro-

politan Paris, located in Saclay.The main objective for the INRIA

Paris-Rocquencourt Research Center is to be a key player

in the major scientific and tech-nological changes underway in the

following three research fields, where it applies its computer science and applied

mathematics skills to conduct leading scientific research over the short and medium term:

Networks and communication systems COMMUNICATINGThe Web, mobile networks, peer-to-peer systems, computing grids and broadband terminals rely on increasingly dense and sophis-ticated network infrastructures. The Center intends to contribute significantly to designing these networks and optimizing their perfor-mance. One of the general objectives of the research is to ensure rapid, reliable, distributed circulation of information at minimal cost to all points of the network in question. The specific focus of research is on the design and mathe-matical analysis of distributed algorithms, the impact of mobility on related protocols and the use of measurements to ensure control.

Reliable software and security PROGRAMMINGOur everyday environment is becoming richer every day in technological products with an important and often invisible software compo-nent - from smart cards to cell phones, auto-mobiles to planes, doctor’s offices to operating rooms. The Center is developing tools for designing increasingly high-quality, efficient and reliable software more rapidly. Its research focuses on high-level languages and program analysis, software specification and valida-tion and constraints solving. It also strives to develop reliable algorithms useful in computer science and calculus, that can be used in widely distributing high-quality software, in particular for engineering design and simulation.

Modeling living systems and the environment COMPUTATIONAL SCIENCES – COMPUTATIONAL MEDICINE New techniques in experimental biology, the remarkable progress in medical imaging, the enormous quantity of satellite data and the intensive deployment of sensors for monitoring ecosystems at all scales require enormous sets of data to be structured and controlled. In order for specialists in these fields to put this progress to good use, complex mathematical models must be developed and analyzed, along with formal computer science methods to validate and manage these models. The Center’s efforts focus on combining these models and data, modeling and simulating organs (such as the heart) and sets of cells (tumor growth), and forecasting changes in the biosphere and soils.


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INRIARennes-BretagneAtlantiqueResearchCenter INRIA Rennes - Bretagne Atlantique Research Center intends to pursue its long-standing partnership policy with higher education establishments and local EPSTs. In addition to consolidating its strengths, however, it also aims to develop significant research work at the frontiers of ICST and other scientific disciplines and strategic fields of applica-tion. The three-way intersection of computer science, telecommunications and multimedia is a prime area of investigation for the Center, as demonstrated by the many collabora-tive efforts with industrial and application partners in this sector, on the regional (Images & networks cluster), national (ANR projects) and international levels. The Center is also heavily involved in European programs, parti-cipating in some forty projects in the �th FP and coordinating three of them.The Research Center focuses on three main priorities that express the scientific challenges to be met in addressing the major issues in our information society and their industrial and application implications:

Mastering large-scale networks and distributed systems COMMUNICATING –PROGRAMMING Achieving this objective involves studying and designing new software, computing and programming models for distributed infras-tructures whose components are only partially

aware of the system as a whole due to its size and possible mobility, heteroge-

neity and dynamism. This requires studying the software mecha-nisms providing virtual access

to resources within computing grids, and new fault tolerance algorithms in

dynamic systems. In general, these large-scale systems pose new challenges in terms of management, surveillance and security.

Design, analysis and compilation of embedded software PROGRAMMING – COMPUTATIONAL ENGINEERING The aim of this priority is to study new paradigms based on the notions of models, aspects, contracts and components for designing and validating embedded software, operations which are becoming increasingly important in such varied fields of application as transportation and telecommunications. Program analysis and testing methods must be improved and integrated in order to guarantee software reliability. Special attention will be paid to the problem of modeling and optimizing non-functional aspects (time, memory and power), which cover a continuum from statically determined systems to dynamically adaptive systems.

Images and multimodal data: from methods to uses INTERACTING – COMPUTATIONAL MEDICINEImages and other media are increasingly present in a variety of contexts for professio-nals and the general public (such as mobile phones and the multimedia Web) and in various scientific fields (medicine, biology, physics, etc.). New methods and sensor networks are also appearing. Some of the main challenges the Center intends to take up include communication, protection, the use of image-related content, videos and multimodal data, the development of interactive virtual environments and the combination of images based on physical and biological models in the life and environmental sciences.


INRIASaclay-Île-de-FranceResearchCenter INRIA Saclay - Île-de-France Research Center will work closely with the System@tic competi-tiveness cluster to achieve future development, participating in the Digiteo RTRA founded by the CEA, CNRS, INRIA, the École Polytechnique, the Paris-Sud University and SUPELEC, in close cooperation with the Paris-Rocquencourt Research Center. The Center will also be buil-ding a strong relationship with the CEA and its partners through the NeuroSpin brain-imaging project conducted in the MediTech competi-tiveness cluster.INRIA Saclay - Île-de-France Research Center will focus on developing three areas of activity:

Software security and reliability PROGRAMMING Improving reliability for the critical compo-nents of computing systems requires deve-loping advanced security models and program analysis methods which will be supported by tools for scaling up. The Center’s work is based

on advanced mathematical knowledge: elliptic curves for cryptography, type

theory as a basis for computer proofs, probabilistic models, etc. It aims to

develop methods and tools to improve user confidence in

computational technolo-gies using a rigorous

mathemat ica l approach.

High-performance computing and distributed knowledge on the Web COMMUNICATING The miniaturization and multiplicity of compu-ting and storage components has fundamen-tally changed data processing and computing models. Data may come from sensor networks and distributed resources on the Web. Finding and organizing data requires new exploration and restitution methods based specifically on learning techniques and innovative interaction models. Computing capacities are increasing, but they rely on heterogeneous, dynamic and distributed components. Using them in high-performance computing requires the develo-pment of new architectures and computing models, such as the grid model. This raises a new set of questions in terms of efficiency, breakdown tolerance, new algorithms and programming models.

Modeling, simulation and optimization of complex dynamic systems MODELINGComplex dynamical systems appear in many fields of natural (physics, biology) and artifi-cial (Internet) science. They can be modeled using various approaches (partial differential equations, evolutionary systems, discrete, continuous, deterministic or stochastic methods, computational or algebraic resolu-tion). The main fields of investigation involve image processing, more specifically medical imaging, shape recognition, the construction of mathematical evolution models for plants and organ aging, as well as models of how the brain works. The optimization and robust control of these systems, and their fault tole-rance, remain difficult problems.


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LecentrederechercheINRIASophiaAntipolis-Méditerranée

INRIA Sophia Antipolis -Mediterranée Research Center is a leading partner in networks of key players in its fields because

of its internationally renowned research teams, its presence in the PACA compe-

titiveness clusters (SCS, Pégase, etc.) and its success in the ANR

and European programs. The Nice-Sophia Antipolis site has

three main objectives: actively participating in the ICST Campus

with the University of Nice-Sophia Antipolis (UNSA) and Eurecom in order to

develop it into an excellence cluster; building synergy between ICST research and medical research, in particular with the UNSA, the Center Antoine-Lacassagne and the CHU teaching hospital; and working actively with a network of companies to offer suggestions for industrial players. The Montpellier site aims to work closely with the INRA, CIRAD and partners of the LIRMM to make its presence sustainable. One organizational objective is to involve INRIA successfully in the founda-tion established by the sustainable agrono-mical and environmental science RTRA to create and develop a “computational plant” program.INRIA Sophia Antipolis - Mediterranée focuses its research in three areas of activity:

Ubiquitous communication and computing COMMUNICATING The proper functioning of networks and mobile entities and the transparency of their uses are vital issues, because the services and applications using them require a ubiqui-tous, safe and reliable network. Developing and operating complex, heterogeneous networks relies on algorithms, protocol design, performance assessment, simulation, formal methods and experimentation platforms. The Center’s research focuses on problems related to security, reliability and robustness, new network architectures (networks-on-chips, peer-to-peer, self-organized networks, overlay

networks, grids) and on exploring resources, in addition to integrating knowledge and services into community networks through the semantic Web.

Computational medicine and biology COMPUTATIONAL MEDICINE – COMPUTATIONAL SCIENCESThe Center aims to design, implement and control computational and computer models of living systems ranging from microbial ecosystems to human body organs and forests and to identify parameters using multi-modal measurements (imaging, biological and biochemical signals). This research requires studying and developing new mathematical and algorithmic tools in cooperation with the fields of biology, medicine, physics and chemistry. The Center will focus on computa-tional modeling of biological, anatomical and physiological systems, imaging and medical robotics to assist with diagnosis and custo-mized therapy, computational neurosciences and the modeling of plants and ecosystems for sustainable development.

Modeling, simulation and interaction with the real world MODELING – INTERACTINGModeling and computational simulation are well established in sophisticated industrial processes (space systems, transport, energy, etc.) and will be used increasingly in various sectors (risk management, industrial secu-rity, urban planning, surgical interventions, physical rehabilitation, gaming, etc.). In many of these areas, the fundamental dimension of interactivity is overlaid. The processes of physical and cognitive interaction between the virtual and real worlds require virtual and enhanced audiovisual environments to be created and rendered and the condi-tions for real-time haptic interaction with users to be met, including the conditions for their evaluation. Robotics is another field in which modeling and simulation are becoming increasingly important for applications such as robot-human interaction, development of service robotics and rehabilitation robotics in immersive environments.


Research, Development and Transfer

4.3 4.3.1 OrganizingResearch

INRIA strongly advocates its organizational model into project-teams, which is widely recognized, cited and adopted by various other foreign organizations. A project-team is a group of limited size (approximately 10 - 25 members) with clearly defined scientific objectives and research programs targeting a focused topic over a set period of time. It is directed by a scientific leader who is responsible for coordinating the work of the entire team. INRIA insists on clear objectives shared by all members of a project-team and on the scientific leadership of project leader, who is responsible for proposing objectives for their project and ensuring that research is focused on them.This form of organization has many advan-tages that the Institute holds dear. The visi-bility and impact of the work carried out in the Institute gains traction by promoting the collective aspect of research and by gathering research scientists into teams with clearly iden-tified goals. It provides levels of flexibility and responsiveness that the Institute has further improved over the past few years by increasing turnover on its research project-teams. The project-teams work toward the three goals of knowledge production, technology develo-pment and technology transfer, and they are assessed on the results in each of these areas. The relationship between knowledge and tech-nology development fulfils social needs and the requirements of scientific research. To further enhance the efficiency of its orga-nization into project-teams, the Institute is increasing its resources for coordinating the work and projects of its eight research centers (the boxes in this chapter identify each Center’s research priorities and their relationship to the strategic plan). This coordination takes the form of scientific events, interdisciplinary research and development work, and wider integrative projects. More effort should be devoted to this area, which combines the work of several project-teams and outside partners, focusing on the challenges set out in this plan and on integration and/or interdisciplinary projects aiming to make ambitious connections between knowledge and development. In order to facilitate this change in directions, the Institute will strive particularly to support

researchers who, after one project-team has come to an end, are considering joining exis-ting or new teams, particularly those who are prepared to adjust their research topics to reflect the priorities of INRIA’ scientific policy. INRIA will encourage the autonomy of junior researchers, providing them with opportu-nities for mobility and greater responsibility, by enabling them to manage collaborative research efforts and exploratory work. In the latter area, the Institute will encourage the emergence of new research work, which is radically different from established topics in the field.INRIA will improve its organizational tools to create an overall vision of its research and development and technology transfer work and to implement its scientific and technological policy. The new responsibilities of the scientific departments, the role of overall coordination played by the head of research and technology transfer for innovation, and the creation of an observatory for the Institute’s scientific work are essential factors in achieving this goal.

4.3.2 TechnologyDevelopment

Technology development is becoming increasingly important in ICST research: meeting the specific needs of research in the knowledge-production process; respon-ding to the economic and social issues; and meeting industrial needs as part of a techno-logy transfer and innovation policy. For INRIA, whose mission closely combines research and technology transfer, technology development is crucial. Research in ICST is becoming increasingly complex; large-scale experimentation is neces-sary to address real problems and develop and validate realistic models. When studying widely distributed computing grids and architectures, for example, it is difficult to simulate the beha-vior of thousands of heterogeneous machines and their interconnections. Experimentation platforms must be built in order to approach problems and evaluate solutions on a real-world basis. Similarly, designing and evaluating new network architectures requires realistic, easily configured platforms, which allow real users to run comparative analyses and control experimental conditions. Robotics research can only be carried out with robots and open

4.� Research, Development and Transfer

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CYCLOPE, a sensor device for virtual reality.

experimental environments. Technological development and experimental platforms are also needed for the Institute’s other priorities, from studying the vulnerabilities of computing systems to virtual reality. Finally, many of the topics in this strategic plan, in particular in computational engineering, computational science and medicine, require the deployment of sensors, actuators, specific instrumenta-tions and embedded processors in substantial experiments.The Institute will be developing experimental platforms for all of these fields, in cooperation with other organizations such as the CEA, CNRS, INRA or INSERM for multi-disciplinary, nation-wide or international issues. These platforms will be open to the national scien-tific community. Developing these platforms clearly requires investing in more than simply off-the-shelf equipment. It demands substan-tial technological development, particularly in terms of software.

Resources Used The Institute will be investing even more, particularly in terms of human resources, to support the technological developments of its teams. The principal means to support this strategy are described in this section.Support for development will be increased by reinforcing the experimentation and develop-ment technical units (EDT’s) and considerably increasing the number of permanent staff and visiting staff positions in these departments. These engineers will be integrated into our project-teams to actively support software and experimental development. In addition to collaborative work with the project-teams, EDT’s will also be responsible for producing, deploying and updating generic software to encourage better software development prac-tices within the Institute, such as software forges and porting platforms.Technology development initiatives (TDI) are a new instrument within INRIA. They fit in with the logic and dynamics of a collabora-tive project and provide common ground for project-teams and development services. These initiatives rely on scientific resources within project-teams, as well as the technical, human and experimental resources managed by the EDT’s. Technical development work is defined and performed jointly by one or

more project-teams and one or more EDT’s, a scientist is in charge of and responsible for the work (except in exceptional circumstances). This work may be conducted jointly by INRIA partners depending on the nature of the work and the partner. The software development operations program is a component of INRIA’s technology transfer and use policy. It aims to facilitate the development and circulation of high-quality software from INRIA research projects and increase its technological impact. The program provides an additional development resource for project-teams in the form of “associate engineers” assigned for two-year periods. This program will be continued.Experimental platforms are technological research resources made available to several project-teams. The software and/or hardware components of a platform are generic and shared. The platform allows teams to share infrastructure, operation and supply costs and also facilitates partnerships between teams by facilitating access, paving the way for more ambitious developments and improving the visibility of research. INRIA already has several experimental platforms in its centers, for robo-tics, virtual reality, computer-assisted vision and distributed computing. To meet scien-tific needs relating to the Institute’s strategic priorities, and particularly to reach the related challenges, some platforms must be modified and others created; for example, a high-perfor-mance computing platform for simulation, updated GRID 5000 equipment and a platform for studying embedded system security are needed. Varying degrees of experimentation on embedded systems, sensor networks and interactive robotics could also be supported by platforms set up as needed, in partnership or as part of national or international initiatives. We will be seeking to streamline management of existing and future platforms with a coor-dinated policy and systematic assessment of their impact. Standardization support will be reinforced and expanded. Standardization work is very important because it improves the visibility of research and helps to publicize it in the world of business. It must be based on develop-ment work that can support standardization proposals, such as software production to demonstrate feasibility and relevance and


provide the benchmarks required for certain types of de facto standardization. In addition to this assistance, a method for making proposals to standardization bodies will be offered to project-teams, mainly in the form of support for engineers. The Institute is already active within standardization and normalization entities in the fields of networks and communication services and information and multimedia data processing, among others. INRIA is a member of W�C, the OMG, ETSI and the JCP, and is also playing an active role in the IETF and the ISO. INRIA intends to consolidate its presence in these organizations and in the decision-making bodies of de facto standardization organizations such as Eclipse.Finally, the intellectual property protection and use policy defined by the technology transfer and innovation strategy (see 4.�.�) will be taken into account explicitly in the initial stages of each development project. It will provide guidance for technical decisions (for example, including open-source components with inherited license obligations), partnership connections and initial protection and/or distri-bution safeguards.

Emphasizing Development WorkIt is important for technology development work to be esteemed as one component of ICST research, alongside the knowledge production demonstrated by top-level inter-national publications. This is why INRIA intends to work with other organizations to implement technological contribution assessment mechanisms, parti-cularly for evaluating software developments. The objective is to have peers offer an asses-sment of software relevance, originality and quality that is recognized within the community, similar to the recognition offered by scientific publications. This will allow software develop-ments to be included effectively in assessing researchers and teams.

4.3.3 TechnologyTransfer

andInnovation

INRIA consistently combines scientific excel-lence with technology transfer. To-date, the Institute’s technology transfer and use policy has been active, decisive and highly succes-sful, in particular for innovative business start-

ups. It intends to pursue a vigorous policy in this area to account for significant changes in the socio-economic environment, new chal-lenges and the increasingly broad issues in relevant business sectors.R&D has become a key factor of competitive-ness. Market position is increasingly depen-dent on technological progress, and innovation management is now at the heart of all industry sectors affected by ICST. Against this backdrop of rapid technological and economic advances, interaction between operational units in companies and pure research must be envi-saged at a very early stage. Technology transfer and innovation cannot occur after knowledge production, but must contribute to identifying and formulating the problems that must be resolved to achieve economic breakthroughs.Early interaction is tightly constrained by shorter and shorter industrial development cycles, in particular in ICST. It requires a shared vision and closeness among teams operating at various points in the development process, from research to design.Paradoxically, research and development support programs, such as European framework and ANR and competitiveness clusters programs, also limit the possibilities for the preliminary interaction required for technology transfer. These programs have given new life to R&D activities by facilita-ting the development of many collaborative initiatives for pre-competitive developments and common-interest tools. The efforts of corporate R&D teams within these programs have weakened their direct partnerships with public research. The Institute’s technology transfer policy must take this redistribution into account and respond to it appropriately by developing areas of special interaction with certain partners, upstream from joint participa-tion in R&D support programs. It is hoped that such bilateral partnerships, based on shared technological perspectives, will lead to joint participation in national and European program initiatives rather than the opposite.INRIA’s technology transfer policy already involves players such as systems specialists, infrastructure manufacturers and telecommu-nications operators. However, the Institute must invest more into the industrial sectors, which have become essential for its strategy,


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including biotechnology, pharmaceutical and medical technologies as well as energy and the environment. Another example is the service sector and its use of information technologies. Service providers, which have not participated in R&D for a long time, are now involved in mediating and deploying innovative techno-logies. They must be properly integrated into INRIA’s technology transfer policy.These considerations have led the Institute to adopt a proactive technology transfer policy for spin-offs and direct technology transfer, identifying key sectors relating to its priorities and adjusting its technology transfer actions as much as possible to their specific charac-teristics. It does so by offering greater support for technology transfer to its project-teams through partnership networks within compe-titiveness clusters, as well as through joint programs with strategic partners.

A Proactive Technology Transfer Strategy INRIA intends to identify potential avenues for technology transfer far in advance and on a case-by-case basis and make choices accor-ding to its innovation objectives, possible deve-lopment initiatives for the target technology and the related technology transfer methods. There are more synergies to be realized between the innovation target, the potentially applicable technology and the implementation strategy. Along with the Institute’s partners, the Institute’s research, technology development and transfer and innovation divisions are fully involved in developing these complex connections, which require multiple layers of interaction between the scientific vision and economic and social requirements.Concrete actions for implementing this strategy will naturally develop both within and around the Institute.Internally, INRIA will analyze technology fore-casts and current research work in order to identify potential technology transfer initiatives as early as possible according to industrial needs. Small groups open to industrial experts and innovators will carry out this process. It will be used to identify a portfolio of innovation initiatives in the form of research incentives, technology development, early technology transfer and possibly intellectual property protection. The corresponding process will use monitoring and management mechanisms for

innovation initiatives, as well as skill mapping, analysis and forecasting resources. INRIA will also provide significant training in entrepre-neurship and innovation internally.The main external initiatives will involve a small number of partners with whom the Institute can meet at a very preliminary stage, for joint vision and technology transfer objectives. These are the Institute’s strategic partnerships, whose strategic dimension rests on several aspects: their ability to develop research chal-lenges relevant to the Institute, their needs for innovative technology used to maintain their industrial advantage, their potential for realizing high-impact benefits by implementing INRIA technologies. With its strategic partners, INRIA wishes to develop program initiatives for every phase of the innovation cycle, from defi-ning topics to implementing solutions for the partner’s processes or products. Initiatives may take several forms, such as joint research/industry laboratories.INRIA’s technology transfer objectives are not limited to its strategic partners. Management of the innovation portfolio will naturally also include seeking partners for direct technology transfer and spin-offs.Technology startups yield essential leve-rage for the transfer policy. Opportunities for new businesses must be sought as widely as possible to facilitate synergy between tech-nical innovations and innovations in the uses and applications of technology. Several tools will be made available to define a proactive process for launching businesses, including a virtual meeting place for working on spin-off projects. Improving the support mechanisms for spin-offs, monitoring and assisting with these projects during their incubation period in order to find test clients and demonstrating the technological and marketing concept will be essential to technology transfer. The direct technology transfer policy is another component of the Institute’s proactive strategy. It requires an understanding of busi-ness sectors and key players’ expectations, as well as prospecting, assistance and support for deploying the transferred technologies. The innovation portfolio must be managed to develop a consistent, logical INRIA offering. The technology transfer process requires upstream study of development procedures and how software is actually transferred.

It is hoped that such bilateral partnerships, based on shared technological perspectives, will lead to joint participation in national and European program initiatives rather than the opposite.


In addition, a technology transfer policy for open-source software and other freely available resources (models, data and docu-ments in various formats) must also be devised and developed as part of this proactive stra-tegy. This involves identifying the leverage expected from free circulation via communities of developers and communities of users. It also requires providing mechanisms and tools to create and lead these communities and to track the process of value creation for services and uses. Achieving these objectives relies on an understanding of economic models for inno-vative startups using open-source software, which is now beginning to be effectively used within INRIA in a few successful spin-offs (for example ActiveEon and GeometryFactory). Finally, the policy described for supporting standardization work in technological develop-ment (see 4.�.2) will also consider technology transfer objectives. Wherever possible, it will be implemented in a way that supports the objectives of our main strategic partners.

Business Sectors and Partnership NetworksThe proactive technology transfer strategy will be consistent with business sector develop-ment plans, accounting for every key player and identifying the initiatives most appropriate for each sector. The Institute intends to work in the areas of telecommunications (infrastruc-ture, services and equipment), energy, trans-portation, sustainable development, defense and health, specifically biotechnology. The ICST sector as a whole will be approached with a view to producing software and high added value services.INRIA’s must improve its position in compe-titiveness clusters, which are open meeting places for collaborative work with large industrial companies and SMEs. The projects undertaken within clusters demonstrate this collaborative dimension through supportive, interdisciplinary technologies such as modeling and verification techniques and security tools. Our short-term objectives, in particular in clusters where INRIA is strongly represented, involve taking a greater part in the decision-making bodies of the clus-ters, improving the clarity and consistency of the projects’ underlying topics, and building strong partnerships with SMEs to disseminate these technologies.

Developing an international technology transfer and industrial partnership policy is another objective of this plan. Several factors come into play, such as the presence of INRIA-supported academic laboratories in emerging countries, the international deployment of industrial partners and the interest of foreign companies in INRIA startups. These objectives will have an impact on the Institute’s intellectual property policy. INRIA will reinforce the mechanisms for protecting and exploiting the intellectual property produced by its teams. These mechanisms materially contribute to raising the profile and visibility of technological development. In addition to software registration procedures, which are fairly well integrated within its teams, INRIA will be implementing a patent-filing policy with a clearly defined technological scope, along with resources for raising awareness, training and assisting researchers. These intel-lectual property protection mechanisms will be supported by developing a clear policy on open-source software (particularly for CECILL licenses) whenever this method of technology distribution is preferable. For instance, it may be chosen for reasons of impact, because communities of developers exist, or to support service activities with high technological or economic added value.

4.3.4 Training

throughResearch

One of INRIA’s essential functions is to support training through research for junior PhD students in computer science and applied mathematics. It does this in close relationship with its partner doctoral schools. PhD students have always had a key role in INRIA’s dynamic organization.To encourage and monitor initiatives in favor of PhD students, the Institute has implemented an active training through research program in each center. INRIA supports the organization of discipline-specific schools for PhD students and junior researchers and also awards grants to PhD student organizations. Sometimes the Institute partners with these associations to collect reliable data on the future of junior PhD graduates after their thesis.INRIA intends to continue to actively support doctoral training, specifically emphasizing the


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quality of theses written within its research project-teams and, more generally, the quality of training received by PhD students and their preparation for entering professional life after their thesis. To this end, the Institute will develop relationships with the doctoral schools to which its researchers and teams are atta-ched. It will also continue to experiment with additional training for PhD students in the form of corporate internships, computer science engineering assistant positions, seminars, participation in summer schools, etc. It will provide ongoing training for its permanent staff in teaching methods, training through research and assisting PhD students. In terms of quantity, the Institute will seek to maintain growth in the number of PhD students accepted, just as it does for permanent resear-chers and research professors in its research centers. It will work with partner universities in France and abroad to attract more foreign students into French PhD courses.The attractiveness of PhD study in ICST deserves special attention. INRIA will work with all of its partners (government minis-tries, universities, engineering schools, local government, companies, etc.) to push for needed salary increases for PhD students, and above all for thesis funding. Recently, the Institute was able to institute a program for funding the PhD students accepted into its project-teams (subsidized INRIA doctoral research contracts, or CORDI-S). This program complements the other options for hosting researchers, including doctoral allowances. It differs in that its aim is to accept foreign PhD or constrained-mobility students who would find it difficult or impossible to meet the schedule and procedures for regular applicants. The CORDI-S program is extremely successful and represents an effective contribution to the attractiveness of studying ICST in France. It will be expanded and, if possible, comple-mented through partnerships with companies and local government.For INRIA to meet its objectives for scientific excellence, both funding and the number of candidates must increase. Several avenues will be pursued, such as running awareness campaigns for young people (secondary schools and university undergraduates), promoting jobs in computer science and mathematics research, specific initiatives to

attract candidates (the proportion of female PhD students has increased slightly but is still low at 18%) and initiatives to increase the international recruitment pool (�8% PhD students were from abroad in 2007, a figure which has been rising constantly since 2002). Finally and most importantly, the Institute will continue to work with its industrial partners to raise the profile of research in their recruitment procedures.Over the next few years, INRIA will be expan-ding its policy of active partnership with doctoral schools. The Institute’s strong desire to participate in the crucial development of national training through research initiatives for ICST demands that it consolidate its rela-tionships with universities and engineering schools. INRIA will encourage its researchers to become more involved in training efforts by providing a substantial ongoing training program in teaching methods and science teaching. In addition to its commitment to doctoral training, INRIA will pursue and broaden its initiatives for hosting postdoctoral researchers in several areas: hosting young researchers for postdoctoral study on one of the Institute’s project-teams, sending young French PhD graduates for postdoctoral study abroad, and mixed arrangements such as those for ERCIM postdoctoral positions. Finally, INRIA will continue to host young engi-neering graduates, to whom it offers introduc-tory-level positions for several years, which provide additional technological training in hands-on research, usually followed by recruit-ment into the industry.

4.3.5 DistributingScientific

InformationandKnowledge

Open ArchivesAccess to scientific information is essential for researchers and society as a whole. The publications of researchers in journals and scientific conference reports announce signi-ficant advances in research, and it is on the basis of these publications that contributions are recognized, teams assessed and funded and their global reputation established. The profound changes in access to information provided by the Internet have dramatically changed research practices. The scientific

Helping the general public understand and adopt scientific and methodological knowledge is a clear necessity in a world where science and technology play a major economic and social role. This issue is particularly critical for ICST.


community has adopted these new tools, taking full advantage of the acceleration of exchanges. In fact, these tools have created a new economic model for scientific publi-cations, which is more effective in spreading scientific knowledge: little by little, costly subs-criptions are being replaced by free access for all readers with relatively little investment required from research organizations. The October 200� Berlin Declaration, which INRIA signed, declares: “For the first time ever, the Internet now offers the chance to constitute a global and interactive representation of human knowledge, including cultural heritage and the guarantee of worldwide access.”This movement toward free access has grown rapidly: a publication’s impact in terms of citations increases substantially if it is freely accessible on the Web and if its longevity is guaranteed by an open archive available through one or more institutions. INRIA is associated with the HAL open archive. With its partners’ research organizations and universities, the Institute is committed to making HAL the shared platform for recording scientific production by its researchers. INRIA encourages its teams to register their work in the HAL-INRIA open archive, which has a specific registration and consultation inter-face for ICST. INRIA hopes to register all of its publications in HAL rapidly, including any publication that can be registered. Several initiatives have been set up to this end, such as technical developments to make HAL a practical, efficient tool, institutional visibility for those registering their work, easy mana-gement of the bibliographical data of teams and researchers and support for registration and training. Finally, the Institute will support the editorial activity of free-access scientific journals in its field and will encourage all scientific publica-tions to transition to free access, including the proceedings of the main conferences in its field.

Diffusion of Knowledge Helping the general public understand and adopt scientific and methodological knowledge is a clear necessity in a world where science and technology play a major economic and social role. This issue is particularly critical for ICST.

Digital technologies have entered all sectors of activity. There is a substantial risk that citizens will feel out of their depth in the demands placed on them to use techno-logy in their daily lives. If they do not clearly understand the issues raised by using certain sensitive applications, they may fail to use it correctly or worse still, lose interest entirely. On the other hand, scientists and engineers often see computer science solely as a tool and fail to take into account the basics and conceptual and fundamental potentials of the field as a whole.This is why research issues and processes must be explained, along with the scientific autonomy of a field, which is indeed more than the visible technology it produces. INRIA is already a key player in scientific culture, and for three years now it has been developing interactive multimedia content and making it freely accessible at www.interstices.info, a website created on the Institute’s initiative and in partnership with the CNRS, universities and the ASTI.Over the next few years, it is vital not only to ensure high levels of ongoing funding, but also to reach a wider audience, particularly among high school students, with this elec-tronic publication on the scientific culture of ICST. It is also essential to increase the diversity of contributions across Europe, so that similar research in other countries and research centers can be combined.INRIA has set the following objectives for the duration of the strategic plan:• in 2007, the Interstices website published

five new documents every month. The Institute will encourage more researchers to contribute, and will assist them with the process of formatting their contributions. The site will feature articles accessible to high school students for use in classes and practices, and will be promoted to teachers. The aim is to double monthly output over a four-year period with the support of a reinforced editorial committee and tech-nical team;

• INRIA will be taking its initiatives for scien-tific culture online in cooperation with the regional CCSTIs (or similar institutions) and the national education ministry. The Institute wishes to expand its presence within secondary schools, and will thus


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expand its efforts involving teachers to all research centers. This includes signing agreements, sponsoring the mathematics Olympiad, organizing lectures by resear-chers, organizing or sponsoring scientific initiatives taken by teachers and distributing teaching resources in schools, such as the ABCs of computer science;

• with its partner universities, INRIA will be supporting the development of subject-specific computational universities to help spread scientific culture and distribute teaching and pedagogical content;

• the Institute will work to improve understan-ding of the challenges and potential of ICST among elected officers and decision-makers and to strengthen national and local public policies in this area;

• in Europe, INRIA will encourage the crea-tion of a network of websites similar to Interstices with its partners. By exchanging or listing their text, image, video and inte-ractive animation content and translating it when necessary, these sites will more easily reach the critical mass needed to ambitiously cover the field of ICST, while remaining highly responsive to the rapid progress in knowledge.

4.3.6 EvaluatingResearch

andTechnologyTransfer

Evaluating project-teams and researchers is essential to scientific life at the Institute, which consistently works to maintain the quality and the rigor of the assessment process. INRIA project-teams are evaluated every four years. This assessment is carried out by topics and nation-wide in order to provide reviewers with a full view of the Institute’s work in a given field. The Institute is particularly attached to this aspect of its scientific life. The process is very demanding for the project-teams, who must position themselves in relation to all the teams working in the same area, no matter what their geographical location. This allows the Institute to maintain an overall vision of its work and assignments, and to define overall strategy and scientific policy.A dozen academic and industrial reviewers, many of them from outside of France, make evaluations during a two-day seminar. The objectives and criteria of assessment include

scientific contributions, technological develo-pments such as software, technology transfer activity, and the contributions of the team to teaching and training through research. The process considers the objectives proposed by each project-team at its inception or renewal for a period of four years. All of INRIA’s work within an area is presented at the seminar for evaluation, in particular joint work between project-teams, and topics receiving excessive or insufficient attention are pointed out.The evaluation report gives the experts’ detailed opinion on the general economy of the topic concerned and their appraisal of each of the project-teams. The teams are invited to comment on the reviews. These docu-ments and evaluations by the Centers’ project committees are used by INRIA Evaluation Committee to draft recommendations on whether or not each project-team should be extended. Once the scientific committee gives its opinion, the process ends with a decision by the INRIA directors to either shut down a given project-team or extend it for a fixed term.INRIA’s overall evaluation process for its project-teams is highly dynamic and effec-tive. The Institute will maintain this evaluation process, in addition to the AERES assessment process for research teams in their geogra-phical context. The latter will provide INRIA with an evaluation of the regional context of each research center.It is important to stress that alongside tradi-tional scientific production through publi-cation, which traditionally uses peer review for assessment, this process must examine and evaluate a very broad range of activities. Software developments must be taken into account, the impact of technology transfer initiatives assessed, and training and mana-gement appraised. Collective responsibilities and inter-team and interdisciplinary scientific leadership tasks must also be evaluated, along with experiences in mobility, efforts to distribute scientific and technological infor-mation to the general public, and all forms of risk-taking. Again, the Institute will study its assessment system in detail to better evaluate techno-logical development, both in improving the assessment of technology transfer and measu-ring its impact.

Evaluating is essential to scientific life at the Institute, which consistently works to maintain the quality and the rigor of the assessment process.


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European and International

Relations

4.4

Viviane Reding, European Commissioner for Information Society and Media, with Michel Cosnard.

4.4.1 INRIA’sCommitment

inEurope

Pursuing a strong commitment to building and developing European research is a major priority for INRIA’s policy. By combi-ning excellence in research and technology transfer, INRIA draws on this commitment to consolidate its position in Europe.

INRIA and Framework ProgramsThe sixth and seventh framework programs represent major challenges for INRIA. The Institute aims to use them to consolidate its strong position in Europe, relying on its expe-rience with previous framework programs. This effort will mainly affect the Information and Communication Technologies priority, for

which the Institute is already working with many European industrial players. The Institute participated in 119 projects for the �th FP, 9� of which were still under way at the end of 2007 and several of which will continue into 2010. The 7th FP, scheduled to run until 201�, has just been launched. 18 new proposals where chosen from the first call for proposals, for a success rate of 2�.9% (compared with 17% Europe-wide). The Institute will continue to be heavily involved in this program.INRIA is also pro-actively involved on the European Research Council (ERC). It encou-rages its junior researchers to apply as soon as a competition is announced in their field, and will continue to do so for future calls for proposals, particularly for experienced researchers. Across Europe, a total of 9,1�7 applications were submitted in all disciplines, including 2� (0.28%) from INRIA. 559 appli-cations were selected for the second stage, � of them (0.54%) from INRIA. In parallel with the FP, some INRIA research centers are developing cross-border exchanges with neighboring institutions. For example, the Lille - Nord Europe Research Center is involved in an initiative under the INTERREG program and is preparing to set up a joint IPT with the CWI in Amsterdam, while the Nancy - Eastern France Research Center is making considerable efforts to strengthen a cross-border partnership between INRIA, the Max Planck Institute, the DFKI, the Fraunhofer Institute, and the Universities of Sarrebrücken, Kaiserslautern, and Luxembourg.

The ERCIM ConsortiumThe ERCIM consortium, which now has 18 members from 18 European countries, is the only organization of its kind in Europe. Over the years, with support from INRIA, ERCIM has become more open to and representative of the scientific and technological commu-nity in the field of ICST, to the point that the European Commission is beginning to rely on it to monitor community research operations and relationships with other regions of the world. The consortium has also improved its international visibility by becoming the European host for the W�C. For all of these reasons, and because of its many task forces

4.4 European and International Relations

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and increasingly successful program for postdoctoral grants, ERCIM is a driving force behind INRIA’s European commitment. It must now consolidate its reputation as an essential tool for promoting ICST throughout Europe.

European Industrial PartnershipsINRIA will pursue efforts beyond the scope of the FP to develop relationships with major European industrial companies that hold leading positions worldwide in areas relating to its research priorities. To this end, the Institute is participating in the Eurêka ITEA and ITEA-2 programs for embedded and distributed software (INRIA project-teams are currently partners for 10 ITEA and ITEA-2 projects). The Institute also pays particular attention to European technological platforms (ETP) in its field, which are of vital importance. One permanent researcher has agreed to serve as the scientific contact for each of these platforms and monitor the ETP’s scientific work and projects. The platforms are: Artemis (Embedded Computing Systems), eMobility (the Mobile and Wireless Communications Technology Platform), EPoSS (European Technology Platform on Smart Systems Integration), EUROP (European Robotics Platform), ISI (Integral Satcom Initiative), NEM (Networked and Electronic Media), NESSI (Networked European Software and Services Initiative) and IMI (Innovative Medicines Initiative). INRIA belongs to the management organizations of these plat-forms and helps to develop their strategic research agendas.The Institute is also keen to ensure a positive outcome for the AIR&D consortium, formed by Philips, Thomson and Fraunhofer, a major success of its European industry partnership policy.

4.4.2 Cooperationwith

Asia,NorthAmericaand

SouthernCountries

INRIA is a world-class institute of excel-lence in its field. As international competi-tion increases and ICST becomes a leading priority in national research policies, it is vital that the Institute expands its international

cooperation by developing partnerships in targeted geographic areas.The main focus of INRIA’s international stra-tegy is making the Institute more attrac-tive and able to recruit and accept foreign students and researchers. INRIA is a strong proponent of hiring foreign researchers for permanent positions, extending invitations to visiting researchers on sabbatical and hosting postdoctoral researchers and students. There are several tools available in this area, such as the internship program.Developing partnerships with leading foreign university and industrial laboratories is a constant factor in international policy. INRIA has several flexible options to achieve this, including the associate teams program, Ministry of Foreign Affairs programs (Marie Curie grants) and programs at other world-wide institutions (NSF, JSPS, CNPQ, etc.).In addition to these general priorities, INRIA organizes its international policy by geogra-phical area.• The strong partnership with North America

is vital given the United States’ expertise in the ICST and the life sciences.

• More cooperative efforts will be deve-loped with China, Hong Kong, Taiwan, Singapore and India. The aim is to quickly and substantially increase the number of people moving from one continent to the other, particularly young people. The LIAMA laboratory in Beijing is a cornerstone of this objective.

• INRIA will continue to support training through research in Africa in general, and North Africa in particular. The objective is to encourage exchanges between resear-chers, co-supervision of theses and joint research projects. The Institute will encou-rage Masters Degree programs to be esta-blished in Africa by sending its researchers on local assignments. This policy is part of the existing partnership and aims to limit brain drain.

• Further efforts will be pursued in South America, particularly Brazil, Chile, Uruguay and Argentina, where there are sizeable skills clusters in computer science and applied mathematics. The usual resources will be used to establish effective coope-ration (calls for joint projects, internships, associate teams, etc.).

Over the FP, INRIA will pursue efforts beyond the scope of the FP to develop relationships with major European industrial companies.


Internal Organization and

Operation

4.5

10th anniversary of LIAMA, Beijing.

Programs INRIA will pursue its four main programs for international relations. The associate teams program, which aims to develop close coope-ration with foreign partners, will be expanded, particularly for Asia. The internship program will encourage the involvement of young students in INRIA research teams to build up a pool of potential scientific colleagues and to increase the international visibility of ICST. Two relatively small programs will also be expanded: the sabbatical visit program, which aims to increase mobility of INRIA researchers to foreign academic and indus-trial laboratories, and the explorers program, which encourages junior researchers to enrich their international experience by facilita-ting short stays in the Institute’s partner laboratories.

The Institute intends to maintain the general organization implemented in late 200�, as described below, for the 2008-2012 period. This organization is divided into three distinct mana-gement levels: research project-teams, research centers (which combine project-teams with research, development and technology transfer support institutions under directors providing both scientific and managerial leadership) and nationally managed administrative services. The latter includes the senior management (CEO and VPs) and nine functional department:• the research department, the technological

development department, the technology transfer and innovation department, the European partnership department and the international relations department. These five scientific department are supervised by the CEO for science and technology;

• the human resources department, the admi-nistrative, financial and assets departmentand the information systems, infrastructure and computing services department. These three department, in addition to the administrative department are supervised by the CEO for administration of resources and services;

• the communications department.The four members of the senior management, the eight research center directors and nine

functional directors form the management committee.Overall management is provided according to a matrix that separates the “operational produc-tion structures,” or research centers and their teams and services, from the “functional lines,” which are operated by the administrative divi-sions; each of these two segments is responsible for part of the Institute’s policy. This leaves the research centers and their project-teams with a great deal of delegated responsibility. Over the coming years, INRIA intends to continue decentralizing its organization by directly invol-ving directors of Research Centers within the management committee. One area for impro-vement will be the matrix pattern of operations, specifically the mechanisms for coordination, reporting and management control (in the broad sense) and required internal assessments. This matrix-based organization is certainly more complex than a straightforward hierarchy of responsibilities. Nonetheless, it is necessary for a research organization that wishes to provide true independence for its centers and project-teams without becoming a federation of independent centers. The administrative divisions play a vital role in ensuring that the Institute’s policy is applied across the board. They will be asked to refocus on management

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The INRIA’s human resources include not only regular staff, researchers, support staff and personnel on short term contracts in different categories, but also the many external employees who are not paid by the Institute but are directly involved in its project-teams, with the same management needs.

and assessment, as well as implementing the decisions, procedures and tools that provide a framework for decentralized management by the research centers themselves under the guidance of center directors. To allow this, these administrative divisions will be relieved of day-to-day operations by concentrating administrative and logistical support functions within the head office administration department established in 2007.This transition relates to the broad guidelines provided in the two preceding sections and the responsibilities of the human resources and support functions. The first part of this document described the constant effort to improve the quality and efficiency of research support and assistance. Aspects of this include pursuing the decentralization policy and applying a quality procedure wherein all players are responsible for management, developing the information system, implementing more efficient methods and tools for management and management control, and sharing a common management culture.

4.5.1 HumanResourcesPolicy

Under its previous strategic plan, the Institute committed to modernizing its administrative approach, which resulted in significant changes in its human resources management policy. Personnel management is no longer an essen-tially administrative task focused on applying rules and regulations, but rather a truly dynamic development function that aims to balance legis-lative requirements with the Institute’s desire to see its staff and skills progress. This transition was achieved using the possibilities offered by the Finance Legislation Framework Law.More than ever before, mobilizing the human resources necessary for research is a major challenge for the Institute. The risks of scientific careers being abandoned by young people, mounting competition between the different stakeholders in French and foreign research to attract the best people, and rapid changes in technologies, related skills and business have made human resources management a key to future success. Relying on its many assets, INRIA will continue to consolidate its human resources policy and systematically review related activities to keep pace with both internal and external changes,

while doing everything in its power to meet the needs of its personnel. For the purposes of this discussion, the INRIA’s human resources include not only regular staff, researchers, support staff and personnel on short term contracts in different categories, but also the many external employees who are not paid by the Institute but are directly involved in its project-teams, with the same management needs. The Institute’s strategic approach to human resources, which requires a considerably more efficient information system (see below), will be organized around three major aspects:• building an employment policy on a pros-

pective vision. Because its organization is constantly changing, the Institute must anti-cipate changes in research work in order to adapt to future scientific challenges. Extensive efforts must be made to analyze the most dramatic changes in research support (compu-ting, development, management, etc.) and the Institute must anticipate developments in positions and skills (obsolete and emer-ging positions, work which can be pooled or outsourced, etc.). This analysis must be extended to include scientific work, such as enhancing career paths, future prospects for PhD students and graduates and the nume-rous French and foreign staff working with INRIA on a temporary basis each year;

• improving collective and individual moni-toring of careers. Existing structures for researchers and individual assessment for support staff will be used as the basis for developing new training and assistance resources that allow individuals to pursue their personal preferences while promoting the Institute’s ambitions. For researchers, this will involve setting guidelines to suggest possible professional career paths, not only in terms of scientific expertise but also managerial skills. For support staff, the annual review process that has been used for several years gives a detailed description of which skills are being used; a multi-year master plan for professional training will facilitate progress by combining collective needs with personal preferences;

• professionalizing management practices. The Institute’s managers will continue to receive support. INRIA has already deve-loped a management handbook; the next step is to set up a true internal “manage-ment school”. In an ever-changing research


environment, managers must have access to training courses right from the outset of their careers and continuously thereafter to help them understand their environment and exercise their responsibilities, provide better management tools, and spread a common culture that facilitates shared objectives.

Initiatives are also being developed to keep in touch with former INRIA staff by setting up and maintaining a network both for professional contacts, particularly with businesses in the sector, and job seeking.Finally, since the involvement of more women in ICST – a sector that attracts considerably fewer of them than do other sectors – would enrich its research, INRIA will do more to promote the participation of women among its scientists, on its decision-making bodies, and in positions of responsibility.With all of these initiatives, it is important to remember that trade union organizations are valuable partners in a strategic approach to human resources management that takes the needs of all staff into account. Productive dialogue between staff and management is needed for both individual and collective success.

4.5.2 InternalOperations

Reliable and Simplified Administrative and Financial ManagementManagement improvement relies on the finan-cial and accounting modernization protocol signed in 200�, which aimed to overhaul and simplify the Institute’s administrative, accoun-ting and financial management. The prospect of certified accounts, as described in the financial security law that INRIA must apply starting in 2009, requires overhauling many internal processes, particularly those relating to investment management, separation of fiscal years, asset assessment, income valuation and debt assessment.Formalized internal control and auditing, for which the Institute has recently developed working methods, will help to improve admi-nistrative quality. Updating documentation for all procedures and operating modes for the new information system, will provide support for everyone involved. Processes will be faster and more reliable once paperless techniques for accounting docu-

ments are implemented, in particular linking invoices with order forms and automating repe-titive tasks.The management system developed as of 2007 will gradually be deployed, providing stakehol-ders and decision-makers with the resources for true management control. This in turn will rein in budgets and streamline support costs, which are currently skyrocketing as INRIA’s operations expand and diversify. Achieving this final objective also requires establishing a purchasing policy that can be combined with analysis of cost factors to develop more efficient budgets. To this end, analytical accounting must be expanded beyond its current use, which focuses mainly on accounting for expenditures in executing European contracts.Management control also entails increased professionalism on the part of stakeholders. A large-scale training plan will be implemented to instill management culture within the organi-zation. This will improve understanding of highly technical tasks, particularly those relating to VAT and assets. We expect that it will improve overall management quality, which has become even more essential in light of account certification requirements.Another key area for improvement in terms of simplifying administration is the management mandates applied to joint research organiza-tions and more generally with INRIA’s partner institutions.

An Information System Extended to All Spheres of ActivityRunning a multi-site and multi-player organiza-tion like INRIA smoothly requires an information system that is much more efficient and complete than at present, or even fully integrated. Such a system favors decentralizing operations to many different responsibility and networking hubs.At the end of 2007, the Institute adopted an “information system orientation plan” to guide the research centers and functional divisions in developing the information system in three major directions over the coming years:• developing a service mentality to improve

efficiency for the various business lines and users by developing new networking methods and increasing accessibility to internal and external resources;

• systematizing a global approach to these services, guaranteeing consistency

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and forward compatibility with two objec-tives: achieving openness and interopera-bility with the information systems of the Institute’s partners information systems, and supplying the synthesized data necessary for management;

• broadly applying a quality procedure to improve the reliability and availability of services and help the organization share skills more effectively.

One priority will be deploying a high-perfor-mance human resources information system (HRIS). It will be extended functionally and modernized in two phases: once the most urgent, short-term needs are met (2008-2009), a more ambitious project will be launched to fully cover all the necessary functions by the end of the strategic plan.Other strategic areas identified for the Institute’s information system include encouraging “total communication” through permanent ultra-high-speed access to resources in all work situations (on INRIA’s sites, on external sites, when traveling in France or abroad); provi-ding staff with a set of adaptable and flexible tools to meet requirements for working over the network (scientific collaboration, project management, document and data sharing, etc.); supporting the work of researchers by providing access to publications and reports and mechanisms for distribution and moni-toring, platform operation, application and contract tracking, etc.; extending the func-tional scope of management tools by making them interoperable with external information systems; developing measurement and mana-gement tools; and developing a computer security policy (PSSI) that reconciles protec-tion requirements with the need for openness and flexibility.

Internal CommunicationsCommunication is a complex and constantly changing task at INRIA, a growing multi-site establishment involved in many partnerships, which encourages high turnover of temporary staff in addition to its vital permanent base of core competencies. In addition to sharing infor-mation, which is one main function, communi-cation provides INRIA with an identity to assist change and coordinate the development of a management culture. Over the last few years, the Institute has adopted information channels

that maintain the delicate balance between diversity and unity: an electronic publication for sharing news briefs among disciplines; a newsletter from the management committee; a network of internal websites dedicated to the project-teams, research centers, business lines and functional types of action; and a policy for welcoming new arrivals that involves the human resources and communications depart-ments of each center, taking the form of an annual newcomers’ seminar and welcome pack available nation-wide. The challenge for the coming years is to encourage all staff to internalize the Institute’s constantly changing focus. In this area, internal communications will serve to unify the Institute, both nationally and within each Center. Existing media are not suitable for this function, since they provide information rather than motivation. INRIA’s 40th anniversary offered an opportunity to launch a far more unifying medium, Code Source, which has been a resounding success. Similarly, preparing for the Computer Science and Society forum in Lille in late 2007 required a great deal of collective effort and offered an opportunity for stimulating discussion about the Institute’s shared values. These efforts must be pursued.Implementing strategic plan, rolling out the mana-gement procedure, developing a quality proce-dure and supporting development for managers are all projects which the Institute intends to pursue in the years ahead. Implementing projects like these inevitably requires change, and the passive resistance to this change that often develops can impede their implemen-tation and affect the expected performance. This is why such sweeping projects must be supported by structured communications. The strategic management of the Institute’s human resources must be visible and shared by all. It is essential that this policy be understood as the Institute experiences massive growth and sets up new research centers. Everyone involved must have the tools necessary to understand their professional environment, which provides meaning, strengthens ties and develops a feeling of belonging and a collective context for all those involved. Further objectives include developing internal communications at the Institute’s head office (which are currently far less developed than at the research centers) and coordinating national and local efforts.

In addition to sharing information, which is one main function, communication provides INRIA with an identity to assist change and coordinate the development of a management culture.


AAERESResearch and higher education evaluation agency

AESEAeronautics, space and embedded systems (competitiveness cluster)

AIIAII Industrial innovation agency

AIR&DAmbient Intelligence Research & Development

ALADDINTechnological development action relating to the GRID 5000 infrastructure

ANRNational research agency

ARCCooperative research action

ARCADIAQuadric, algorithm, implementation and application arrangements

ARTEMISProgram for Embedded Systems R&D in Europe

ARTEMISIAARTEMIS Industrial Association

ASTIFrench association for information science and technology

CCADPConstruction and Analysis of Distributed Processes

CADComputer Assisted Design

CAPRISecure networks of sensors (cf. Minalogic)

CARIAfrican conference on research in computer science

CASPCritical Assessment of techniques for protein Structure Prediction

CCSTIScientific, technical and industrial culture center

CDRIOfficer in charge of the development of industrial relations

CEAAtomic energy center

CEA-DSVAtomic energy center - Life sciences division

CECILLFrench open source software license [for Ce(A)C(nrs)I(NRIA)L(ogiciel)L(ibre)]

CEOChief executive officer

CERMICSComputer science and scientific compu-ting research and teaching center

CHUTeaching hospital

CIRADCenter for international cooperation in agronomical research for development

CITICenter for innovations in telecommunica-tion and service integration

CMAPCenter of applied mathematics

CNPQConselho Nacional de Desenvolvimento Científico e Tecnológico (Brazil)

CNRSNational scientific research center

CORDI-SState-subsidized INRIA doctoral research contract

CPERState-region project contract

CPUFrench university chancellors’ conference

CPUCentral Processing Unit

G lossary


AERES>FTTH

CSAILComputer Science and Artificial

Intelligence Laboratory (MIT, United

States)

CSTBFrench building research center

CWICentrum voor Wiskunde en Informatica

(Netherlands)

DDARPADefense Advanced Research Projects

Agency (United States)

DFKIDeutsche Forschungszentrum für

Künstliche Intelligenz (Germany)

DGAFrench national armament agency

DGEFrench business agency

DirDRIFrench agency for development and

industrial relations

DNADeoxyribonucleic acid

DTNDelay-Tolerant Networking

EEADSEuropean Aeronautic Defense and Space company

ECGElectrocardiogram

EDFÉlectricité de France

EDPPartial differential equations

EDTExperimentation and development department

EEGElectroencephalogram

EIFFELEvolved Internet Future for European Leadership

ELMExtended length message

ENSÉcole normale supérieure

EPoSSEuropean Platform on Smart Systems Integration

EPSTPublic scientific and technological institution

ERCEuropean Research Council

ERCIMEuropean Research Consortium for Informatics and Mathematics

ETPEuropean Technology Platform

ETSIEuropean Telecommunications Standards Institute

EUROFIBanking and Finance in Europe

EUROPEuropean Robotics Platform

FFCEBusiness competitiveness fund (see DGE)

FINDFuture Internet Network Design (see NSF)

FIREFuture Internet Research and Experimentation

FTFrance Telecom

FTR&DFrance Telecom Research and Development

FTTHFiber To The Home


GGENIGlobal Environment for Networking

Innovations (see NSF)

GETTelecommunications schools group

GISScientific interest group

GMDGesellschaft für Mathematik und

Datenverarbeitung (Germany)

GMOGenetically modified organism

GNPGross national product

GPUGraphics Processing Unit

HHALHyper Article Online

HQEHigh energy quality

HRISHuman resources information system

IICSTInformation and communication science and technology

IECNInstitut Elie Cartan (in Nancy)

IEEEInstitute of Electrical and Electronics Engineers

IETFInternet Engineering Task Force

IFNNational forestry inventory

IFREMERFrench institute of research for the exploi-tation of the sea

IMBBordeaux mathematics institute

IMIInnovative Medicines Initiative

INANational audiovisual institute

INPGNational polytechnic institute in Grenoble

INPLNational polytechnic institute in Lorraine

INRANational institute for agricultural research

INRIANational institute for research in computer science and automatic control

INSANational institute of applied science

INSERMNational institute for health and medical research

INTERREGAcronym for a European program on cooperation between border regions

IPv6Internet Protocol v�

IPTINRIA project-team

IRIAResearch institute for computer science and automatic control

IRISAResearch institute for computer science and random systems

IRSNInstitute for radiological protection and nuclear safety

ISIIntegral Satcom Initiative

ISOInternational Standards Organization

G lossary


GENI>NEMS

ITAEngineers, technicians and administrative staff

ITEAInformation Technology for European Advancement

ITERInternational Thermonuclear Experimental Reactor

JJADJean-Alexandre Dieudonné laboratory

JCPJava Community Process

JSPSJapan Society for the Promotion of Science

LLABRIBordeaux laboratory for computer science research

LAGISAutomatic control, computer engineering and signal processing laboratory

LIAMAFranco-Chinese laboratory for computer science, automatic control and applied mathematics

LIENSÉcole normale supérieure computer science laboratory (see ENS)

LIFLLille pure computer science laboratory

LIGGrenoble computer science laboratory

LINANantes Atlantique computer science laboratory

LIPParallel computer science laboratory

LIP6University of Paris � computer science laboratory

LIRMMMontpellier computer science, robotics and microelectronics laboratory

LIXÉcole Polytechnique computer science laboratory

LJKJean Kuntzmann laboratory

LMAPau applied mathematics laboratory

LMDDynamic meteorology laboratory

LORIALorraine laboratory for computer science and applications research

LRIComputer science research laboratory

LSVSpecification and verification laboratory

MMEMSMicroelectromechanical systems

MERCATORMercator Ocean public interest group

MIGPPau geosciences imaging and modeling

laboratory

MINALOGICMicro-nano technologies and embedded

software intelligence (competitiveness

cluster)

MITMassachusetts Institute of Technology

(United States)

MOSTMinistry of Science and Technology

(China)

MPGMax Planck Gesellschaft (Germany)

NNEMNetworked and Electronic Media

NEMSNano Electro Mechanical Computers


NESSINetworked European Software and

Services Initiative

NICTANational Information and Communication

Technologies Australia

NIHNuclear magnetic resonance

NISTNational Institute of Standards and

Technology (United States)

NITRDNetworking and Information Technology

Research and Development Program

(United States)

NMRNuclear magnetic resonance

NOEMSNano Opto Electro Mechanical Systems

NS3National Security Swath Ship (DCNS

group)

NSFNational Science Foundation (United

States)

NWONederlanse Organisatie voor

Wetenshappelijk Onderzoek (Netherlands)

OODLSoftware development operation

OLSROptimized Link State Routing protocol

OMGOBJECT Management Group

ONERANational office for aerospace studies and

research

PP2PPeer to peer

PACAProvence - Alpes - Côte d’Azur region

PCRDResearch and development framework

program

PFEExperimental platforms

PRESResearch and higher education cluster

PSSIInformation systems security policy

RR&DResearch and development

RATPThe Paris transport authority

RFIDRadio-frequency identification

RIITCross border tourist route networks (see INTERREG)

RTRAThematic advanced research network

SSARIMASupport for computer science and mathe-matics research in Africa

SCSSecure communication systems (competi-tiveness cluster)

SICONOSEuropean Modeling, Simulation and Control of Non-smooth Dynamical Systems project

SISSpontaneous information system

SMESmall and medium-sized companies

G lossary


NESSI>W3C

SNCFFrench national railways

SOCsSystems-On-Chips

STMabbreviation for STMicroelectronics

TTDITechnological development action

UUCSDUniversity of California, San Diego (United States)

UDLRUnidirectional Link Routing protocol

UNSAUniversity of Nice - Sophia Antipolis

USTLLille university of science and technology

VVATValue added tax

WW3CWorld Wide Web Consortium

Document published by the General Management of INRIA

Layout:

Photo credits: © INRIA / J. Wallace, C. Lebedinsky, J.M. Ramès, A.S. Douard - © CNES / Distribution Spot Image / 1998 - © Airbus S.A.S. / 2008 - © Frédéric Cirou - © DigitalVision

ISBN 2-7261-1296 8 January 2008