DIVERSIFY Ecology-inspired software diversity for distributed adaptation in CAS 1

DIVERSIFY

Ecology-inspired software diversity for distributed adaptation in CAS

1

•1 slide about the main idea / challenge

•1 slide about objectives

•2 slides about budget

•1 slide about IP

•3 slides about impact (meta design, adaptive systems, soft diversity)

•1 slide about WP2

•1 slide about advances in soft diversity (update slide 24)

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Collaborative adaptive systems

•Large-scale

•Open

•Dynamic

•Eternal

•Heterogeneous environments

•Face unpredictable situations

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4

CASs are a form of complex system

An essential property: diversity

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Main idea

•Diversity is an essential characteristic of complex systems to adapt to unpredicted changes in their environment

•Ecosystems, economical systems, social systems, etc.

•CASs are deployed in environments that evolve in uncontrolled and unpredicted ways

BUT•Software diversity remains very little explored as an insurance principle to adapt to changes

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•DIVERSIFY brings together researchers from the domains of software-intensive distributed systems and ecology in order to translate ecological concepts and processes into software design principles

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Consortium

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Ecological board

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M. Hutchings (Univ. of Sussex)

B. Kunin(Univ. of Leeds)

E. Thébault(CNRS)

C. Melian (EAWAG)

Objective

DIVERSIFY aims at formalizing and experimenting new models and synthesis mechanisms for software diversity in collaborative adaptive systems, based on the ecological concept of biodiversity. The goal is to increase adaptive capacities in the face of structural and environmental variations.

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WP structure

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Progress in software engineering

•Software diversity

•synthesis and spontaneous emergence of software diversity

•Dynamic adaptation

•leveraging diversity to reach specific goals

•Distributed adaptation

•models@runtime for the collaboration of heterogeneous, distributed software entities

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Expected impact - science

•Genuine ecological inspiration for distributed adaptation

•Continuous evolution and approximate correctness

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Expected impact - society

•Software-intensive, collaborative systems are pervasive in our society

•DIVERSIFY aims at experimenting in smart cities

•Greater robustness of other forms of CAS

•assisted living, emergency systems, etc.

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Impact, management and dissemination

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Management structure

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Budget

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Efforts

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IP management

•Foreground will be disseminated in open source

•Details about background will be specified in consortium agreement

•CA is based on DESCA

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Infrastructure for collaboration

•Social source code and document repository

•Private and public github repositories

•Shared Folder (SparkleShare)

•Private and public wiki

•Meeting White board (etherpad)

•Announcement (twitter)

•Website (drupal)

•Visio conference (INRIA visioconference bridge)

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Work plan

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WP1 Ecological modeling

•Objectitves

•ensure knowledge transfer from ecologists

•formalize and validate software diversity models

•formalize and validate software distributed adaptation mechanisms

•establish a tight connection with WP2 and WP3 through the collection of state-of-the-art models of biodiversity and distributed adaptation

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WP2

•Objectives:

•models of software diversity in CASs

•synthesize diversity.

•lifecycle of diversity

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WP3 Objectives and organization

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Environment with diversity

Application 1 Application 2

Application N

Diversity-based Adaptation

T3.4Diversity-

Driven Adaptation

Diversity Model(model at runtime)

T3.3 Monitoring

T.3.2

WP2

WP2 Diversity

WP4

WP1

•SoTA: self-* Systems

•Objectives

• Capture Application Needs

• Discover/Monitor Diversity

• Trigger Application Adaptations

Work Package 4

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T2: Simulation and experiment

T3: Evaluation and report

T1: Domain analysis and scenario design

D4.1: Scenario design and system investigation

D4.2: Smart City SimulatorD4.3: Simulator document and analysis

D4.4: Experiment report

WP1: Ecological Modeling

Reference for scenarios

Provides evaluation criteria

WP2&3: Software diversity and distributed adaptation

Application and feedback

WP5 Dissemination, collaboration and exploitation

•Main objectives

•ensure collaboration inside the project

•disseminate results outside the project

•communicate on the program and particate in the FOCAS CA

•3 tasks:

•Infrastructure and support for project communication

•Scientific dissemination and exploitation

•Collaboration26

WP6 Management

•Will assure:

•global quality;

•timely (and in respect with the budget) finalization of the deliverables and reports; and

•good communication, collaboration and transparency between the partners and towards the European Commission.

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Contributions to SoTA

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Background and positioning

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Software diversity

•The main objective of DIVERSIFY is to develop mechanisms that introduce diversity at runtime, in association with the mechanisms that select the relevant level of diversity according to environmental conditions.

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Diversify & Autonomic Computing

•Autonomic Computing

•Adjusting the system to its environment

•How to prune the search space?

•DIVERSIFY

•Adjusting the environment to the system

•Diversified search space => Easy to find a good-enough solution

Degree of DiversityProbability to find solutions

Reacti

on

tim

eTim

e n

eeded t

o fi

nd a

solu

tion

Low probability to find a

good-enough solution

Higherprobability to find a

good-enough solution

Diversify

ThingML language•Modelling language for the IoT

•Based on well established formalisms

• Architecture models

• Asynchronous messaging

• State machines

• Imperative action language

•Targets the whole spectrum of devices of the Future internet (from microcontrollers to cloud)

•A good candidate language for experimenting with diversity

•Open-source and available at http://www.thingml.org33

ThingML as a bridge between IoT and IoS

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Smart City Research at TCD

Dependability, trustworthy, privacy…

Dynamic optimization of urban resources

Water manage-

ment

Urban traffic control

Community energy

management

Smart phones

In-vehicle systems

CCTV In-house devices

...

...

Data brokerage and simulation

City watch

On-going projects

MDDSV

Personal Cities

LAMP

Use case, CityWatch with Intel

trustworthy participatory & opportunistic sensing

Collecting & disseminating sensor data

Sensor data processing and city environment simulation

model driven development and formal methods

Integrated simulation environment on vehicles and traffics Formalisation of distributed coordination

self-organising of electrical devices on the smart grid

Simulation on mainstream grid simulator, GridLAB-D

Multi-agent, single policyDWL benchmarked

for collaborative and coordinated smart vehicle applications

DYSARM

Runtime models to support the adaptation of urban scale systems

Started from the domain analysis of water distribution systems

Language-based framework for runtime models

services on urban resource

s

Dynamic adaptatio

n

Runtime

models

Constraint-driven self-adaptation with user preference

Lightweight M@R framwork for building Distributed Adaptive System

M@R Runtimes for Distributed and Heterogeneous adaptive systems

Extensible Virtual System Infrastructure

Resilient Software infrastructure based on diversity

Kevoree in nutshell 1/2

Kevoree in nutshell 2/2

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One clonal network

Connexions Information transfer, storage

Ramets Resource acquisition

The clonal plant model

•More than 70% are clonal with particular network forms

•These network forms are constitued of two units with different functions

heterogeneous environments

Ramet specialization (diversification of

functions)

Low resource environments


•In heterogeneous environments, apparition of diversity within the network

•Importance of heterogeneity grain, environment predictability, patch contrasts

Scale of signal integration

Treshold for response

development (trade-off cost vs. theoretical benefit at the network level)

Local environmental cues(change in environmental conditions, stress, local disturbance)

Local response(growth, (reproduction))

Global network performance(efficiency in resource acquisition (-> biomass), network survival)


•Two way for diversity development:

•spontaneous (age dependent)

•response to environmental changes

Relation with close projects

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Relation with PerAda and Awareness

•Common

• Focused on the self-awareness and self-adaptation of software-based systems

• Started from large data, services, and learning-based technologies

• Share some common topics (such as e-Mobility with ACENS, a project under Awareness)

•Difference

• We focus more on the urban infrastructure (water, energy), rather than the social aspects

• We focus more on software (services), rather than control (robots)

• We are from a software engineering perspective, utilizing MDE, middleware technology, etc.

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Related projects - AWARENESS 1/5

• Sapere = Self-aware Pervasive Service Ecosystems

o Model and deploy services as autonomous individuals in an ecosystem of other services, data sources, and pervasive devices.

Self-aware components and a general nature-inspired interaction model

Decentralized self-* algorithms

Spatial self-organization, self-composition, and self-management

• Diversify will takes inspiration from Ecology by involving Ecologists in the project, and will mainly focus on leveraging the diversity and food web properties from Ecosystems to build reliable systems


• Cocoro = Collective Cognitive Robots

o Swarm intelligence inspire from natural and biology phenomenon

Application to: robots, underwater vehicles ...

• Diversify will not focus on this type problems.

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• ASCENS : Autonomic Service-Component ensembles

• Combine formal method and optimal resource usage promised by autonomic computing

• Apply to robotics, cloud computing and e-Vehicles

• Diversify has a totally different approach build self-adaptive resilient applications inspired by eco-systems

• EPICS : Engineering Proprioception in Computing Systems

• Proprioception (coming from psychology) is the basic ability to collect and maintain information about state and progress

• Transfer knowledge from another science to computer science

• Diversify follow the same process for transferring knowledge from another science to computer science, but will focus on transferring knowledge from Ecology and will integrate Ecologist as core partners of the project

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• Recognition: Relevance and cognition for self-awareness in a content-centric Interneto inspired by the cognitive process of human

o using psychological and cognitive science apply to Internet content

• Diversify is not doing the same thing ...


• SYMBRION : Symbiotic Evolutionary Robot Organismso swarm & collective robot systems -

evolutionary robot organisms apply to flots of robots Symbrion is cited in PerADA and Awareness A bit particular because the website speaks

about 3 projects (one in Awareness and the other in PerADA) + Symbrion Enlarged EU + un projet REPLICATOR

Related Project - PerAda 1/5

• ALLOW : Adaptable Pervasive Flowso New programming paradigm for developing

adaptable pervasive flows

• Compared to Diversify : Use traditionnal techniques of Context-aware programming and so on.


• ATRACO : Adaptive and Trusted Ambient Ecologieso A context-aware artefact, appliance or device uses sensors to perceive its context of operation and applies an ontology to interpret this context. It also uses internal trust models and fuzzy decision making mechanisms to adapt its operation to changing context.

• Diversify will works with Ecologist to really transfer knowledge from Ecology to computer science.


• FRONTS : Foundations of Adaptive Networked Societies of Tiny Artefactso foundational algorithmic

o unifying scientific framework and a coherent set of design rules, for global systems resulting from the integration of autonomous interacting entities, dynamic multi-agent environments and ad-hoc mobile networks.


• REFLECT: Responsive Flexible Collaborating Ambiento sensing users and their mood and intentions + human behavioural patterns = environmental awareness ==> used for adaptation

• Very different to what we are doing in Diversify


• SOCIALNETS: Social networking for pervasive adaptationo how social networks can be exploited for the

delivery and acquisition of content, including issues of security and trust

• Very different to what we are doing in Diversify

Documents

DIVERSIFY Ecology-inspired software diversity for distributed adaptation in CAS 1