Skip to main content
SpringerLink
Log in

MAPE-K patterns for self-adaptation in cyber-physical systems

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Cyber-physical systems (CPS) are characterized with their concurrency, heterogeneity and time sensitivity. In this context, it is crucial to have self-adaptive CPS systems in order to manage changing in their internal and external environment and supporting new requirements. Also, CPS systems are known with their restricted connectivity, and consequently, they must perform a decentralized adaptation. This is added to the general complexity of modeling the adaptation process. In fact, the MAPE-K (Monitoring, Analysis, Planning, Execution and Knowledge) control loop model has been identified as a crucial element for realizing self-adaptation in software systems. To respond to the design challenge of self-adaptive CPS, we propose a set of decentralized MAPE-K design patterns to help designer in building such complex systems thanks to software design patterns which provide a general reusable solution to a commonly occurring problem. In this paper, we provide a set of decentralized patterns to model CPS using the refinement technique. For this purpose, we proposed a standard notation based on the UML modeling language to describe the different MAPE-K patterns for decentralized control in self-adaptive CPS. We illustrate our approach by modeling the smart parking application using the coordinated control pattern.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Availability of data and materials

All data generated or analyzed during this study are included in this published article

Notes

  1. https://github.com/MarwaHachicha15/MOGEVE.

References

  1. Abeywickrama DB, Hoch N, Zambonelli F (2013) Simsota: engineering and simulating feedback loops for self-adaptive systems. In: Proceedings of the International C* Conference on Computer science and Software Engineering, C3S2E ’13, page 67–76, New York, NY, USA, Association for Computing Machinery

  2. Abeywickrama DB, Hoch N, Zambonelli F (2014) Engineering and implementing software architectural patterns based on feedback loops. Scalable Comput Pract Exp. Vol. 15

  3. Abeywickrama DB, Hoch Ni, Zambonelli F (2014) An integrated eclipse plug-in for engineering and implementing self-adaptive systems. In: 2014 IEEE 23rd International WETICE Conference, pp 3–8

  4. Abeywickrama DB, Zambonelli F (2012) Model checking goal-oriented requirements for self-adaptive systems. In: 2012 IEEE 19th International Conference and Workshops on Engineering of Computer-Based Systems, pages 33–42

  5. Jean-Raymond A, Michael B, Stefan H, Son HT, Farhad M, Laurent V (2010) Rodin: an open toolset for modelling and reasoning in event-b. Int J Softw Tools Technol Transf 12(6):447–466

    Article  Google Scholar 

  6. Basile F, Chiacchio P, Coppola J (2016) A colored timed petri net model for a cyber-physical view of automated warehouse systems. In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), pages 1–8

  7. Ben Said M, Hadj Kacem Y, Kerboeuf M, Abid M (2020) An MDE-based approach for self-adaptive RTES model generation. Cluster Comput 23(2):925–951

    Article  Google Scholar 

  8. dan Rubel D, Wren J, Clayberg E (2012) The eclipse graphical editing framework (GEF). Addison-Wesley Professional, Boston

    Google Scholar 

  9. Han J-CXD-S, Yang Q-L, Ma G-L (2020) Easymodel: a refinement-based modeling and verification approach for self-adaptive software. J Comput Sci Technol 35(5):1016

    Article  Google Scholar 

  10. Engelsberger M, Greiner T (2015) Software architecture for cyber-physical control systems with flexible application of the software-as-a-service and on-premises model. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pages 1544–1549, March

  11. Garro A, Tundis A, Bouskela D, Jardin A, Thuy N, Otter M, Buffoni L, Fritzson P, Sjölund M, Schamai W, Olsson H (2016) On formal cyber physical system properties modeling: a new temporal logic language and a modelica-based solution. In: 2016 IEEE International Symposium on Systems Engineering (ISSE), pages 1–8

  12. Gassara A, Bouassida RI, Jmaiel M (2013) Towards a multi-scale modeling for architectural deployment based on bigraphs. In: European Conference on Software Architecture, pages 122–129. Springer, Berlin, Heidelberg

  13. Gassara A, Bouassida RI, Jmaiel M (2017) A tool for modeling sos architectures using bigraphs. In: Proceedings of the Symposium on Applied Computing, pp 1787–1792

  14. Graja I, Kallel S, Guermouche N, Cheikhrouhou S, Kacem AH (2020) A comprehensive survey on modeling of cyber-physical systems. Concurr Comput Pract Exp. 32(15)

  15. Hachicha M, Halima RB, Kacem AH (2016) Modeling and verifying self-adaptive systems: a refinement approach. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, October 9-12, 2016, pp 3967–3972. IEEE

  16. Marwa H, Riadh Ben H, Ahmed Hadj K (2018) Modelling, specifying and verifying self-adaptive systems instantiating MAPE patterns. Int J Comput Appl Technol 57(1):28–44

    Article  Google Scholar 

  17. Li G, Song D, Liao L, Sun F, Du J (2014) Learning automata-based adaptive web services composition. In: 2014 IEEE 5th international Conference on Software Engineering and Service Science, pp 792–795

  18. Li T, Tan F, Wang Q, Lei B, Cao J-N, Liu X (2014) From offline toward real time: a hybrid systems model checking and cps codesign approach for medical device plug-and-play collaborations. IEEE Trans Parallel Distrib Syst 25(3):642–652

    Article  Google Scholar 

  19. Neema S, Simko G, Levendovszky T, Porter J, Agrawal A, Sztipanovits J(2014) Formalization of software models for cyber-physical systems. In: Stefania G, Nico P, (Eds). Proceedings of the 2nd FME Workshop on Formal Methods in Software engineering, FormaliSE 2014, Hyderabad, India, June 3, 2014, pages 45–51. ACM

  20. Mangharam RPM, Lee I (2012) Model-driven safety analysis of closed-loop medical systems. IEEE Trans Industr Inform. Vol. 10

  21. Seiger FNR, Keller C, Schlegel T (2015) Modelling complex and flexible processes for smart cyber-physical environments. J Comput Sci 10:137–148

    Article  Google Scholar 

  22. Sahli H, Ledoux T, Rutten É (2019) Modeling self-adaptive fog systems using bigraphs. In: SEFM 2019 : 17th International Conference on Software Engineering and Formal Methods, volume 12226 of Software Engineering and Formal Methods. SEFM 2019. Lecture Notes in Computer Science, pages 252–268, Oslo, Norway, September

  23. Schütt B, Braun T, Otten S, Sax E(2020) Sceml: a graphical modeling framework for scenario-based testing of autonomous vehicles. In: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, page 114–120, New York, NY, USA, Association for Computing Machinery

  24. Seiger R, Huber S, Heisig P, Assmann U (2016) Enabling self-adaptive workflows for cyber-physical systems. In: Schmidt Rainer, Guédria Wided, Bider Ilia, Guerreiro Sérgio (eds) Enterprise, business-process and information systems modeling. Springer International Publishing, Cham, pp 3–17

    Chapter  Google Scholar 

  25. Simko G, Levendovszky T, Maroti M, Sztipanovits J (2014) Towards a theory for cyber-physical systems modeling. In: Ralf Lämmel, Walid T (Eds) Proceedings of the 4th ACM SIGBED International Workshop on Design, Modeling, and Evaluation of Cyber-Physical Systems, CyPhy 2014, Berlin, Germany, April 14-17, 2014, pages 56–61. ACM

  26. Simko G, Lindecker D, Levendovszky T, Jackson EK, Neema S, Sztipanovits J(2013) A framework for unambiguous and extensible specification of dsmls for cyber-physical systems. In: Jerzy WR (Ed) 20th IEEE International Conference and Workshops on Engineering of Computer Based Systems, ECBS 2013, Scottsdale, AZ, USA, April 22-24, 2013, pages 30–39. IEEE Computer Society, 2013

  27. Sinreich D (2006) An architectural blueprint for autonomic computing

  28. Steinberg D, Budinsky F, Paternostro M, Merks (eds) (2009) EMF: Eclipse Modeling Framework 2.0, 2nd edn. Addison-Wesley Professional, Boston

    Google Scholar 

  29. Weyns D, Schmerl B, Grassi V, Malek S, Mirandola R, Prehofer C, Wuttke J, Andersson J, Giese H, Goschka KM (2013) Software engineering for self-adaptive systems II: International Seminar, Dagstuhl Castle, Germany, October 24-29, 2010 Revised Selected and Invited Papers, chapter on Patterns for Decentralized Control in Self-Adaptive Systems, pages 76–107. Springer Berlin Heidelberg, Berlin, Heidelberg

Download references

Funding

No funding was received for conducting this study.

Author information

Authors and Affiliations

  1. ReDCAD, National Engineering School of Sfax, University of Sfax, B.P. 1173, 3038, Sfax, Tunisia

    Riadh Ben Halima, Marwa Hachicha, Ahmed Jemal & Ahmed Hadj Kacem

Authors
  1. Riadh Ben Halima
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marwa Hachicha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ahmed Jemal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed Hadj Kacem
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Riadh Ben Halima.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ben Halima, R., Hachicha, M., Jemal, A. et al. MAPE-K patterns for self-adaptation in cyber-physical systems. J Supercomput 79, 4917–4943 (2023). https://doi.org/10.1007/s11227-022-04828-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-022-04828-2

Keywords

Search

Navigation