Modeling For Sustainability: Or How to Make Smart CPS Smarter?

SEMINAR @ CWI (ALE MEETING), AMSTERDAM, NL.

MODELING FOR SUSTAINABILITYOr How to Make Smart CPS Smarter?

BENOIT COMBEMALEPROFESSOR, UNIV. TOULOUSE, FRANCE

HTTP://COMBEMALE.FR [email protected]@BCOMBEMALE

Complex Software-Intensive Systems

Modeling for SustainabilityBenoit Combemale @ CWI, Nov. 2017

Software intensive systems

▸ Multi-engineering approach▸ Domain-specific modeling▸ High variability and customization ▸ Software as integration layer▸ Openness and dynamicity

Aerodynamics

Authorities

Avionics

SafetyRegulations

Airlines

PropulsionSystem

MechanicalStructure

EnvironmentalImpact

NavigationCommunications

Human-Machine

Interaction

3

Multipleconcerns, stakeholders,

tools and methods

4

Aerodynamics

Authorities

Avionics

SafetyRegulations

Airlines

PropulsionSystem

MechanicalStructure

EnvironmentalImpact

NavigationCommunications

Human-Machine

Interaction

Heterogeneous Modeling

Model-Driven Engineering


Distribution

« Service Provider Manager »

Notification Alternate Manager

« Recovery Block Manager »

ComplaintRecovery Block

Manager

« Service Provider

Manager »

Notification Manager

« Service Provider Manager »

Complaint Alternate Manager

« Service Provider

Manager »

Complaint Manager

« Acceptance Test Manager »

Notification Acceptance Test

Manager

« Acceptance Test Manager »

Complaint Acceptance Test

Manager

« Recovery Block Manager »

NotificationRecovery Block

Manager

« Client »

User Citizen Manager

Fault tolerance Roles

ActivitiesViews

Contexts

Security

Functional behavior

Bookstate : StringUser

borrow

return

deliver

setDamagedreserve

Use case

PlatformModel Design

ModelCode Model

Change one Aspect and Automatically Re-Weave:From Software Product Lines…..to Dynamically Adaptive Systems

J. Whittle, J. Hutchinson, and M. Rouncefield, “The State of Practice in Model-Driven Engineering,” IEEE Software, vol. 31, no. 3, 2014, pp. 79–85.

"Perhaps surprisingly, the majority of MDE examples in our study followed domain-specific modeling paradigms"

Model-Driven Engineering


"A clear challenge, then, is how to integrate

multiple DSLs."

J. Whittle, J. Hutchinson, and M. Rouncefield, “The State of Practice in Model-Driven Engineering,” IEEE Software, vol. 31, no. 3, 2014, pp. 79–85.


Globalization of Modeling Languages

Supporting coordinated use of modelinglanguages leads to what we call the globalizationof modeling languages, that is, the use of multiple

modeling languages to support coordinateddevelopment of diverse aspects of a system.

Benoit Combemale, Julien DeAntoni, Benoit Baudry, Robert B. France, Jean-Marc Jezequel, Jeff Gray, "Globalizing Modeling Languages," Computer, vol. 47, no. 6, pp. 68-71, June, 2014


Globalization of Modeling Languages

• DSMLs are developed in an independent mannerto meet the specific needs of domain experts,

• DSMLs should also have an associated frameworkthat regulates interactions needed to support collaboration and work coordination acrossdifferent system domains.

- 8

Benoit Combemale, Julien DeAntoni, Benoit Baudry, Robert B. France, Jean-Marc Jezequel, Jeff Gray, "Globalizing Modeling Languages," Computer, vol. 47, no. 6, pp. 68-71, June, 2014


Globalization of Modeling Language

- 9

• Context: new emerging DSML in open world⇒impossible a priori unification⇒require a posteriori globalization

• Objective: socio-technical coordination to support interactions across different system aspects

⇒Language-based support for technical integration of multiples domains⇒Language-based support for social translucence

• Community: the GEMOC initiative (cf. http://gemoc.org)

"Globalizing Domain-Specific Languages," Combemale, B., Cheng, B.H.C., France, R.B., Jézéquel, J.-M., Rumpe, B. (Eds.). Springer, Programming and Software Engineering, Vol. 9400, 2015.


The GEMOC Initiative

-10

An open and international initiative to

• coordinate (between members)

• disseminate (on behalf the members)

worldwide R&D efforts on the globalization of modeling languages

http://gemoc.org

@gemocinitiative


The GEMOC Studio

-11

Design and integrate your executable DSMLs

http://gemoc.org/studioLanguageWorkbench

ModelingWorkbench

Edit, simulate and animate your heterogeneous models


The GEMOC Community

-12


From Software Systems

▸ software design models for functionaland non-functional properties

Engineers

System Models

Software


To Cyber-Physical Systems

▸ multi-engineering design modelsfor global system properties

▸ models @ runtime (i.e., includedinto the control loop) for dynamicadaptations

Engineers

System Models Cyber-PhysicalSystem

sensors actuators

Physical System

Software

<<controls>><<senses>>


To Smart Cyber-Physical Systems

▸ analysis models (incl. large-scale simulation, constraint solver) of the surrounding contextrelated to global phenomena (e.g. physical, economical, and social laws)

▸ predictive models (predictive techniques fromAI, machine learning, SBSE, fuzzy logic)

▸ user models (incl., general public/communitypreferences) and regulations (political laws)

Engineers

System Models SmartCyber-Physical System

Context

sensors actuators

Physical System

Software



MDE for Smart CPS Development

▸ Convergence of engineering and scientific models

▸ A modeling framework to support the integration of data from sensors, open data, laws, regulations, scientific models (computational and data-intensive sciences), engineering models and preferences.

▸ Domain-specific languages (DSLs) for socio-technical coordination:▸ to engage engineers, scientists, decision makers, communities

and the general public▸ to integrate analysis/predictive/user models into the control

loop of smart CPS


Sustainability Systems

▸ Sustainability systems are smart-CPS managing resource production, transport and consumption for the sake of sustainability

▸ Ex: smart grids, smart city/home/farming, etc.

▸ Sustainability systems

▸ must balance trade-offs between the social, technological, economic, and environmental pillars of sustainability

▸ involve complex decision-making with heterogeneous analysis models, and large volumes of disparate data varying in temporal scale and modality


MDE for Sustainability Systems

▸ Scientific models are used to understand sustainability concerns and evaluate alternatives (what-if/for scenarios)

▸ Engineering models are used to support the development and runtime adaptation of sustainability systems.

How to integrate engineering and scientific models in a synergistic fashion to support informed decisions, broader engagement, and dynamic adaptation in sustainability systems?

Modeling for SustainabilityB. Combemale, B. Cheng, A. Moreira, J.-M. Bruel, J. Gray

In MiSE @ ICSE , 2016


MDE for Sustainability Systems

1st Modelling For Sustainability Workshop @ Bellairs, 2016

Policy makers(e.g., mayor)

Communities(e.g., farmers)

General public(e.g., individuals)

open data regulations

physical laws

explore the future

andmake it happen

The Sustainability Evaluation ExperienceR (SEER)



Sustainability System(e.g., smart farm)

(

Context

sensors actuators

Production/Consumption

System (e.g. farm)

Software


▸ Smart Cyber-Physical Systems



Heuristics-Laws

Scientists

Open DataScientific Models / Physical Laws (economic, environmental, social)

SEER


(

Context

sensors actuators


System (e.g. farm)

Software

<<controls>><<senses>><<supplement

field data>>

<<feed>>

<<integrate>>

<<explore model relations (tradeoff,

impact and conflict)>>

▸ Based on informed decisions▸ with environmental, social and economic laws▸ with open data



Heuristics-Laws

Scientists

Open Data

General Public(e.g., individuals) Policy Makers

(e.g., mayor)

MEEs("what-if" scenarios)

Scientific Models / Physical Laws (economic, environmental, social)

SEER


(

Context

sensors actuators


System (e.g. farm)

Software

<<controls>><<senses>>Communities(e.g., farmers)

<<supplementfield data>>

<<provide configuration, preferences, questions>>

<<present possible future and variable indicators>>

<<feed>>

<<integrate>>



▸ Providing a broader engagement▸ with "what-if" scenarios for general public and policy makers



Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>



▸ Supporting automatic adaptation▸ for dynamically adaptable systems



Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>



▸ Application to health, farming system, smart grid…



Heuristics-Laws

Scientists

Open Data


(e.g., mayor)



SEER


(

Context

sensors actuators


System (e.g. farm)

Software


<<adapt>>




<<feed>>

<<integrate>>



Farmers

Agronomist

IrrigationSystem

in collaboration with

MDE in Practice for Computational ScienceJean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène RaynalIn International Conference on Computational Science (ICCS), 2015

- 26https://github.com/gemoc/farmingmodeling

FARMING SYSTEM MODELING

Modeling for Sustainability – B. Combemale (Univ. Rennes 1) – December 4th, 2016


Take Away Messages

▸ From MDE to SLE▸ Language workbenches support DS(M)L development

▸ On the globalization of modeling languages▸ Integrate heterogeneous models representing different engineering

concerns▸ Language interfaces to support structural and behavioral relationships

between domains (i.e., DSLs)

▸ From software systems to smart CPS▸ Interactions with the physical world limited to (i.e., fixed, in closed world)

control laws and data from the sensors▸ What about the broader context in which the system involves? ▸ Physical / social / economic laws▸ Predictive models▸ Regulations, user preferences


Conclusion

▸ Integration of scientific models in the control loop of smart CPS is key to provide more informed decisions, a broader engagement, and eventually relevant runtimereconfigurations

▸ SEER is a particular instantiation of such a vision for sustainability systems


Open Challenges

▸ Diversity/complexity of DSL relationships▸ Far beyond structural/behavioral alignment, refinement, decomposition▸ Separation of concerns vs. Zoom-in/Zoom-out

▸ Live and collaborative (meta)modeling▸ Minimize the round trip between the DSL specification, the model, and its

application (interpretation/compilation)▸ Model experiencing environments (MEEs): what-if/for scenarios, trade-off

analysis, design-space exploration

▸ Integration of analysis and predictive models into DSL semantics▸ Towards unpredictable languages▸ Specify the correctness envelope to avoid over-specification▸ Identify plastic computation zones▸ Vary the execution flow of the program

"If you believe that language design can significantly affect the quality of software systems, then it should follow that language design can also affect the quality of energy systems. And if the quality of such energy systems will, in turn, affect the livability of our planet, then it’s critical that the languagedevelopment community give modeling languages the attention theydeserve." − Bret Victor (Nov., 2015), http://worrydream.com/ClimateChange

Modeling for Sustainability

Abstract.

Various disciplines use models for different purposes. An engineering model, including asoftware engineering model, is often developed to guide the construction of a non-existentsystem. A scientific model is created to better understand an existing phenomenon (i.e., analready existing system or a physical phenomenon). An engineering model mayincorporate scientific models to build a smart cyber-physical system (CPS) that require anunderstanding of the surrounding environment to decide of the relevant adaptation toapply. Sustainability systems, i.e., smart CPS managing resource production, transport andconsumption for the sake of sustainability (e.g., smart grid, city, farming system…), aretypical examples of smart CPS. Due to the inherent complex nature of sustainability thatmust delicately balance trade-offs between social, environmental, and economic concerns,modeling challenges abound for both the scientific and engineering disciplines.

In this talk, I will present a vision that promotes a unique approach combining engineeringand scientific models to enable informed decision on the basis of open and scientificknowledge, a broader engagement of society for addressing sustainability concerns, andincorporate those decisions in the control loop of smart CPS. I will introduce a researchroadmap to support this vision that emphasizes the socio-technical benefits of modeling.


Hack your own languages?Join us in the MDE/SLE group of the CNRS IRIT lab, in a freshly rebuilt campus of the warm city of Toulouse!

Open Positions for PhD and Postdoc

BENOIT COMBEMALEPROFESSOR, UNIV. TOULOUSE, FRANCE

HTTP://COMBEMALE.FR [email protected]@BCOMBEMALE