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) 2

Collaborative adaptive systems Large-scale Open Dynamic Eternal Heterogeneous environments Face unpredictable situations 3

4 CASs are a form of complex system

An essential property: diversity 5

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 6

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 7

Consortium 8

Ecological board 9 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. 10

WP structure 11

Progress in software engineering Software diversity synthesis and spontaneous emergence of software diversity Dynamic adaptation leveraging diversity to reach specific goals Distributed adaptation for the collaboration of heterogeneous, distributed software entities 12

Expected impact - science Genuine ecological inspiration for distributed adaptation Continuous evolution and approximate correctness 13

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. 14

Impact, management and dissemination 15

Management structure 16

Budget 17

Efforts 18

IP management Foreground will be disseminated in open source Details about background will be specified in consortium agreement CA is based on DESCA 19

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) 20

Work plan 21

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 22

WP2 Objectives: models of software diversity in CASs synthesize diversity. lifecycle of diversity 23

WP3 Objectives and organization 24 Environment with diversity Application 1 Application 2 Application N Diversity-based Adaptation T3.4 Diversity- Driven Adaptation Diversity Model (model at runtime) T3.3 Monitoring T.3.2 WP2 Diversity WP4 WP1 SoTA: self-* Systems Objectives Capture Application Needs Discover/Monitor Diversity Trigger Application Adaptations

Work Package 4 25 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 Simulator D4.3: 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 Collaboration 26

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. 27

28

Contributions to SoTA 29

Background and positioning 30

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. 31

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 Diversity Probability to find solutions Reaction time Time needed to find a solution Low probability to find a good- enough solution Higher probability 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 33

ThingML as a bridge between IoT and IoS 34

Smart City Research at TCD Dependability, trustworthy, privacy… Dynamic optimization of urban resources Water manage- ment Urban traffic control Community energy management Smart phonesIn-vehicle systemsCCTV 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 policy DWL 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 resources Dynamic adaptation Runtime models Constraint-driven self- adaptation with user preference

Kevoree in nutshell 1/2

Kevoree in nutshell 2/2 38

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 The clonal plant model 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) The clonal plant model Two way for diversity development: spontaneous (age dependent) response to environmental changes

Relation with close projects 42

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. 43

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

Related projects - AWARENESS 2/5 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. 45

Related projects - AWARENESS 3/5 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 46

Related projects - AWARENESS 4/5 Recognition: Relevance and cognition for self-awareness in a content-centric Internet o inspired by the cognitive process of human o using psychological and cognitive science  apply to Internet content Diversify is not doing the same thing...

Related projects - AWARENESS 5/5 SYMBRION : Symbiotic Evolutionary Robot Organisms o 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 Flows o New programming paradigm for developing adaptable pervasive flows Compared to Diversify : Use traditionnal techniques of Context-aware programming and so on.

Related Project - PerAda 2/5 ATRACO : Adaptive and Trusted Ambient Ecologies o 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.

Related Project - PerAda 3/5 FRONTS : Foundations of Adaptive Networked Societies of Tiny Artefacts o 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.

Related Project - PerAda 4/5 REFLECT: Responsive Flexible Collaborating Ambient o sensing users and their mood and intentions + human behavioural patterns = environmental awareness ==> used for adaptation Very different to what we are doing in Diversify

Related Project - PerAda 5/5 SOCIALNETS: Social networking for pervasive adaptation o 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