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Modeling for Smart Cyber-Physical Systems (Jan 26th, 2016)

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Talk given at the CPS Day, organized by CPSE-Labs, SysML France and the GDR GPL in Toulouse, January 26th, 2016

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Modeling for Smart Cyber-Physical Systems (Jan 26th, 2016)

  1. 1. Benoit Combemale (Inria & Univ. Rennes 1) http://people.irisa.fr/Benoit.Combemale benoit.combemale@irisa.fr @bcombemale Jean-Michel Bruel (Univ. Toulouse) http://jmb.c.la bruel@irit.fr @jmbruel in collaboration with INRA and OBEO, and the support of the GEMOC initiative Modeling for Smart Cyber-Physical Systems Application to Sustainability Systems
  2. 2. Complex Software-Intensive Systems Software intensive systems - 2Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 • Multi-engineering approach • Some forms of domain-specific modeling • Software as integration layer • Openness and dynamicity
  3. 3. Aerodynamics Authorities Avionics Safety Regulations Airlines Propulsion System Mechanical Structure Environmental Impact Navigation Communications Human- Machine Interaction 3 Multiple concerns, stakeholders, tools and methods
  4. 4. 4 Aerodynamics Authorities Avionics Safety Regulations Airlines Propulsion System Mechanical Structure Environmental Impact Navigation Communications Human- Machine Interaction Heterogeneous Modeling
  5. 5. Model-Driven Engineering (MDE) Distribution « Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery 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 » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged res erv e Use case Platform Model Design Model Code Model Change one Aspect and Automatically Re-Weave: From Software Product Lines… ..to Dynamically Adaptive Systems - 5Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  6. 6. Model-Driven Engineering (MDE) - 6 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. Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 "Perhaps surprisingly, the majority of MDE examples in our study followed domain-specific modeling paradigms" Distribution « Service Provider Manager » Notification Alternate Manager « Recovery Block Manager » Complaint Recovery 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 » Notification Recovery Block Manager « Client » User Citizen Manager Fault tolerance Roles Activities Views Contexts Security Functional behavior Book state : StringUser borrow return deliver setDamaged res erv e Use case Platform Model Design Model Code Model Change one Aspect and Automatically Re-Weave: From Software Product Lines… ..to Dynamically Adaptive Systems
  7. 7. From Software Systems Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 7 Engineers System Models Software • software design models for functional and non-functional properties
  8. 8. To Cyber-Physical Systems Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 8 Engineers System Models Cyber-Physical System sensors actuators Physical System Software <<controls>><<senses>> • multi-engineering design models for global system properties • runtime models (i.e., included into the control loop) for dynamic adaptations
  9. 9. To Smart Cyber-Physical Systems Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 9 Engineers System Models Smart Cyber-Physical System Context sensors actuators Physical System Software <<controls>><<senses>> • analysis models (incl. large-scale simulation, constraint solver) of the surrounding context related to global phenomena (e.g. physical laws) • probabilistic models (predictive techniques from AI, machine learning, SBSE) • user models (incl., general public/community preferences) and regulations (incl., economic/social/political laws)
  10. 10. • analysis models (incl. large-scale simulation, constraint solver) of the surrounding context related to global phenomena (e.g. physical laws) • probabilistic models (predictive techniques from AI, machine learning, SBSE) • user models (incl., general public/community preferences) and regulations (incl., economic/social/political laws) To Smart Cyber-Physical Systems Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 10 Engineers System Models Smart Cyber-Physical System Context sensors actuators Physical System Software <<controls>><<senses>> An MDE-Based Approach for Data Integration and Socio- Technical Coordination in Smart CPS Development
  11. 11. A MDE-based approach to develop Smart CPS Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 11 • Convergence of engineering and scientific models • A modeling framework to support the integration of data from sensors, open data, laws/regulation, scientific models, engineeering models and preferences. • Domain-specific languages for socio-technical coordination • to engage engineers, scientist, decision makers, communities and general public • to integrate analysis/probabilistic/user models into the control loop of smart CPS
  12. 12. Using MDE in Smart-CPS Development - 12 • Cyber-Physical Systems Engineers System Models Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  13. 13. Using MDE in Smart-CPS Development - 13 • Based on informed decisions • with environmental, social and economic laws • with open data Heuristics-Laws Scientists Open Data Engineers System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  14. 14. Using MDE in Smart-CPS Development - 14 • Providing a broader engagement • with "what-if" scenarios for general public and policy makers Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  15. 15. Using MDE in Smart-CPS Development - 15 • Supporting automatic adaptation • for dynamically adaptable systems Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  16. 16. Using MDE in Smart-CPS Development - 16 • Application to health, farming system, smart grid… Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  17. 17. Farming System Modeling - 17 Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Farmers Agronomist Irrigation System in collaborationwith Jean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène Raynal, "MDE in Practice for Computational Science," International Conference on Computational Science (ICCS), 2015. Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016
  18. 18. Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 Farming System Modeling - 18 Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Farmers Agronomist in collaborationwith climate serieVegetal and animal lifecycle farm definition activity description hydric stress Irrigation System Jean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène Raynal, "MDE in Practice for Computational Science," International Conference on Computational Science (ICCS), 2015.
  19. 19. Farming System Modeling - 19 Heuristics-Laws Scientists Open Data Engineers General Public Policy Makers MEEs ("what-if" scenarios) System Models Physical Laws (economic, environmental, social) Simulation Tool (incl. constraint solver, prediction tool, etc.) Sustainability System (e.g., smart grid) Context sensors actuators Energy Production/ Consumption System Software <<controls>><<senses>> Farmers Agronomist in collaborationwith climate serieVegetal and animal lifecycle farm definition activity description hydric stressbiomass growth, water consomption and activity schedule water to be irrigated Irrigation System Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 Jean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène Raynal, "MDE in Practice for Computational Science," International Conference on Computational Science (ICCS), 2015.
  20. 20. - 20 https://github.com/gemoc/farmingmodeling FarmingSystemModeling Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 • Heterogeneous modeling and simulation • Graphical animation and debugging (incl. breakpoints, timeline, step forward/backward, stimuli management, etc.) • Multi-dimensional and efficient trace management • Concurrency simulation and formal analysis
  21. 21. Open Challenges Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 21 • Diversity/complexity of DSL relationships • far beyond structural and behavioral alignment, refinement, decomposition • Separation of concerns vs. Zoom-in/Zoom-out • Live and collaborative modeling • minimize the round trip between the DSL specification, the model, and its application (interpretation/compilation) • Model experiencing environnements • Integration of analysis and probabilistic models into DSL semantics
  22. 22. towards a LiveModelingEnvironment enabling a broader engagement and informed decisions in dynamicallyadaptableresource managementsystems Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 - 22
  23. 23. - 23Modeling for Smart CPS – B. Combemale (INRIA & Univ. Rennes 1) – Jan. 2016 "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 language development community give modeling languages the attention they deserve." − Bret Victor (Nov., 2015), http://worrydream.com/ClimateChange

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