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SEMINAR @ CWI (ALE MEETING), AMSTERDAM, NL.
MODELING FOR SUSTAINABILITY
Or How to Make Smart CPS Smarter?
BENOIT COMBEMALE...
Complex Software-Intensive Systems
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Software
intensive
system...
Aerodynamics
Authorities
Avionics
Safety
Regulations
Airlines
Propulsion
System
Mechanical
Structure
Environmental
Impact
...
4
Aerodynamics
Authorities
Avionics
Safety
Regulations
Airlines
Propulsion
System
Mechanical
Structure
Environmental
Impac...
Model-Driven Engineering
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Distribution
« Service Provider
Man...
Model-Driven Engineering
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
"A clear challenge, then,
is how to...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Globalization of Modeling Languages
Supporting coordinated u...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Globalization of Modeling Languages
• DSMLs are developed in...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Globalization of Modeling Language
- 9
• Context: new emergi...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The GEMOC Initiative
-
10
An open and international initiati...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The GEMOC Studio
-
11
Design and integrate your
executable D...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The GEMOC Community
-
12
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
From Software Systems
▸ software design models for functiona...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
To Cyber-Physical Systems
▸ multi-engineering design models
...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
To Smart Cyber-Physical Systems
▸ analysis models (incl. lar...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
MDE for Smart CPS Development
▸ Convergence of engineering a...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Sustainability Systems
▸ Sustainability systems are smart-CP...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
MDE for Sustainability Systems
▸ Scientific models are used ...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
MDE for Sustainability Systems
1st Modelling For Sustainabil...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Sustainabil...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Heuristics-...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Heuristics-...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Heuristics-...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Heuristics-...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
The Sustainability Evaluation ExperienceR (SEER)
Heuristics-...
- 26
https://github.com/gemoc/farmingmodeling
FARMING SYSTEM MODELING
Modeling for Sustainability – B. Combemale (Univ. Re...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Take Away Messages
▸ From MDE to SLE
▸ Language workbenches ...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Conclusion
▸ Integration of scientific models in the control...
Modeling for Sustainability
Benoit Combemale @ CWI, Nov. 2017
Open Challenges
▸ Diversity/complexity of DSL relationships
...
"If you believe that language design can significantly affect the quality of
software systems, then it should follow that ...
Modeling for Sustainability
Abstract.
Various disciplines use models for different purposes. An engineering model, includi...
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 o...
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Modeling For Sustainability: Or How to Make Smart CPS Smarter?

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Various disciplines use models for different purposes. An engineering model, including a software engineering model, is often developed to guide the construction of a non-existent system. A scientific model is created to better understand an existing phenomenon (i.e., an already existing system or a physical phenomenon). An engineering model may incorporate scientific models to build a smart cyber-physical system (CPS) that require an understanding of the surrounding environment to decide of the relevant adaptation to apply. Sustainability systems, i.e., smart CPS managing resource production, transport and consumption for the sake of sustainability (e.g., smart grid, city, farming system…), are typical examples of smart CPS. Due to the inherent complex nature of sustainability that must 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 engineering and scientific models to enable informed decision on the basis of open and scientific knowledge, a broader engagement of society for addressing sustainability concerns, and incorporate those decisions in the control loop of smart CPS. I will introduce a research roadmap to support this vision that emphasizes the socio-technical benefits of modeling.

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

  1. 1. SEMINAR @ CWI (ALE MEETING), AMSTERDAM, NL. MODELING FOR SUSTAINABILITY Or How to Make Smart CPS Smarter? BENOIT COMBEMALE PROFESSOR, UNIV. TOULOUSE, FRANCE HTTP://COMBEMALE.FR BENOIT.COMBEMALE@IRIT.FR @BCOMBEMALE
  2. 2. Complex Software-Intensive Systems Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 Software intensive systems ▸ Multi-engineering approach ▸ Domain-specific modeling ▸ High variability and customization ▸ 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 Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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 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"
  6. 6. Model-Driven Engineering Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 "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.
  7. 7. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 Globalization of Modeling Languages Supporting coordinated use of modeling languages leads to what we call the globalization of modeling languages, that is, the use of multiple modeling languages to support coordinated development 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
  8. 8. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 Globalization of Modeling Languages • DSMLs are developed in an independent manner to meet the specific needs of domain experts, • DSMLs should also have an associated framework that regulates interactions needed to support collaboration and work coordination across different 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
  9. 9. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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.
  10. 10. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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
  11. 11. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The GEMOC Studio - 11 Design and integrate your executable DSMLs http://gemoc.org/studio Language Workbench Modeling Workbench Edit, simulate and animate your heterogeneous models
  12. 12. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The GEMOC Community - 12
  13. 13. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 From Software Systems ▸ software design models for functional and non-functional properties Engineers System Models Software
  14. 14. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 To Cyber-Physical Systems ▸ multi-engineering design models for global system properties ▸ models @ runtime (i.e., included into the control loop) for dynamic adaptations Engineers System Models Cyber-Physical System sensors actuators Physical System Software <<controls>><<senses>>
  15. 15. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 To Smart Cyber-Physical Systems ▸ analysis models (incl. large-scale simulation, constraint solver) of the surrounding context related to global phenomena (e.g. physical, economical, and social laws) ▸ predictive models (predictive techniques from AI, machine learning, SBSE, fuzzy logic) ▸ user models (incl., general public/community preferences) and regulations (political laws) Engineers System Models Smart Cyber-Physical System Context sensors actuators Physical System Software <<controls>><<senses>>
  16. 16. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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
  17. 17. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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
  18. 18. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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 Sustainability B. Combemale, B. Cheng, A. Moreira, J.-M. Bruel, J. Gray In MiSE @ ICSE , 2016
  19. 19. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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 and make it happen The Sustainability Evaluation ExperienceR (SEER)
  20. 20. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption System (e.g. farm) Software <<controls>><<senses>> ▸ Smart Cyber-Physical Systems
  21. 21. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) Heuristics-Laws Scientists Open Data Scientific Models / Physical Laws (economic, environmental, social) SEER Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption 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
  22. 22. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) 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 Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption System (e.g. farm) Software <<controls>><<senses>>Communities (e.g., farmers) <<supplement field data>> <<provide configuration, preferences, questions>> <<present possible future and variable indicators>> <<feed>> <<integrate>> <<explore model relations (tradeoff, impact and conflict)>> ▸ Providing a broader engagement ▸ with "what-if" scenarios for general public and policy makers
  23. 23. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) 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 Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption System (e.g. farm) Software <<controls>><<senses>>Communities (e.g., farmers) <<adapt>> <<supplement field data>> <<provide configuration, preferences, questions>> <<present possible future and variable indicators>> <<feed>> <<integrate>> <<explore model relations (tradeoff, impact and conflict)>> ▸ Supporting automatic adaptation ▸ for dynamically adaptable systems
  24. 24. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) 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 Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption System (e.g. farm) Software <<controls>><<senses>>Communities (e.g., farmers) <<adapt>> <<supplement field data>> <<provide configuration, preferences, questions>> <<present possible future and variable indicators>> <<feed>> <<integrate>> <<explore model relations (tradeoff, impact and conflict)>> ▸ Application to health, farming system, smart grid…
  25. 25. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 The Sustainability Evaluation ExperienceR (SEER) 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 Sustainability System (e.g., smart farm) ( Context sensors actuators Production/ Consumption System (e.g. farm) Software <<controls>><<senses>>Communities (e.g., farmers) <<adapt>> <<supplement field data>> <<provide configuration, preferences, questions>> <<present possible future and variable indicators>> <<feed>> <<integrate>> <<explore model relations (tradeoff, impact and conflict)>> Farmers Agronomist Irrigation System in collaboration with MDE in Practice for Computational Science Jean-Michel Bruel, Benoit Combemale, Ileana Ober, Hélène Raynal In International Conference on Computational Science (ICCS), 2015
  26. 26. - 26 https://github.com/gemoc/farmingmodeling FARMING SYSTEM MODELING Modeling for Sustainability – B. Combemale (Univ. Rennes 1) – December 4th, 2016
  27. 27. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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
  28. 28. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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 runtime reconfigurations ▸ SEER is a particular instantiation of such a vision for sustainability systems
  29. 29. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017 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
  30. 30. "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
  31. 31. Modeling for Sustainability Abstract. Various disciplines use models for different purposes. An engineering model, including a software engineering model, is often developed to guide the construction of a non-existent system. A scientific model is created to better understand an existing phenomenon (i.e., an already existing system or a physical phenomenon). An engineering model may incorporate scientific models to build a smart cyber-physical system (CPS) that require an understanding of the surrounding environment to decide of the relevant adaptation to apply. Sustainability systems, i.e., smart CPS managing resource production, transport and consumption for the sake of sustainability (e.g., smart grid, city, farming system…), are typical examples of smart CPS. Due to the inherent complex nature of sustainability that must 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 engineering and scientific models to enable informed decision on the basis of open and scientific knowledge, a broader engagement of society for addressing sustainability concerns, and incorporate those decisions in the control loop of smart CPS. I will introduce a research roadmap to support this vision that emphasizes the socio-technical benefits of modeling. Modeling for Sustainability Benoit Combemale @ CWI, Nov. 2017
  32. 32. 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 COMBEMALE PROFESSOR, UNIV. TOULOUSE, FRANCE HTTP://COMBEMALE.FR BENOIT.COMBEMALE@IRIT.FR @BCOMBEMALE

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