Decentralized Dynamic Adaptation for Service-Based Collective Adaptive Systems

  • Antonio Bucchiarone
  • Martina De Sanctis
  • Annapaola Marconi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10380)


Modern service-based systems are progressively becoming more heterogeneous. They form a socio-technical system, composed of distributed entities, software and human participants, interacting with and within the environment. These systems operate under constant perturbations that are due to unexpected changes in the environment and to the unpredictable behavior of the participants. We argue that for a service-based system to be resilient, adaptation must be collective. Multiple participants must adapt their behavior in concert to respond to critical runtime impediments. In this work, we present a framework for the modeling and execution of large-scale service-based Collective Adaptive Systems, where adaptation needs are solved in a decentralized and collective manner.


  1. 1.
    Bozhinoski, D., Di Ruscio, D., Malavolta, I., Pelliccione, P., Tivoli, M.: FLYAQ: enabling non-expert users to specify and generate missions of autonomous multicopters. In: 30th IEEE/ACM ASE (2015)Google Scholar
  2. 2.
    Bozhinoski, D., Malavolta, I., Bucchiarone, A., Marconi, A.: Sustainable safety in mobile multi-robot systems via collective adaptation. In: IEEE SASO, pp. 172–173 (2015)Google Scholar
  3. 3.
    Bucchiarone, A., Dulay, N., Lavygina, A., Marconi, A., Raik, H., Russo, A.: An approach for collective adaptation in socio-technical systems. In: IEEE SASO Workshops, pp. 43–48 (2015)Google Scholar
  4. 4.
    Bucchiarone, A., Marconi, A., Mezzina, C.A., Pistore, M., Raik, H.: On-the-fly adaptation of dynamic service-based systems: incrementality, reduction and reuse. In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 146–161. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-45005-1_11 CrossRefGoogle Scholar
  5. 5.
    Bucchiarone, A., De Sanctis, M., Marconi, A., Pistore, M., Traverso, P.: Design for adaptation of distributed service-based systems. In: Barros, A., Grigori, D., Narendra, N.C., Dam, H.K. (eds.) ICSOC 2015. LNCS, vol. 9435, pp. 383–393. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-48616-0_27 CrossRefGoogle Scholar
  6. 6.
    Bucchiarone, A., Sanctis, M.D., Marconi, A., Pistore, M., Traverso, P.: Incremental composition for adaptive by-design service based systems. In: Proceedings of the IEEE ICWS, pp. 236–243 (2016)Google Scholar
  7. 7.
    Coppo, M., Dezani-Ciancaglini, M., Venneri, B.: Self-adaptive monitors for multiparty sessions. In: PDP 2014, pp. 688–696. IEEE (2014)Google Scholar
  8. 8.
    De Nicola, R., Loreti, M., Pugliese, R., Tiezzi, F.: A formal approach to autonomic systems programming: the SCEL language. TAAS 9(2), 7 (2014)CrossRefGoogle Scholar
  9. 9.
    Far, B.H., Wanyama, T., Soueina, S.O.: A negotiation model for large scale multi-agent systems. In: IRI, pp. 589–594 (2006)Google Scholar
  10. 10.
    Hennicker, R., Klarl, A.: Foundations for ensemble modeling - the helena approach - handling massively distributed systems with elaborate ensemble architectures. In: Specification, Algebra, and Software - Essays Dedicated to Kokichi Futatsugi, pp. 359–381 (2014)Google Scholar
  11. 11.
    IBM: An architectural blueprint for autonomic computing. Technical report, IBM (2006)Google Scholar
  12. 12.
    Lalanda, P., McCann, J.A., Diaconescu, A.: Autonomic Computing - Principles, Design and Implementation. Undergraduate Topics in Computer Science. Springer, London (2013). doi: 10.1007/978-1-4471-5007-7 Google Scholar
  13. 13.
    Levi, P., Kernbach, S.: Symbiotic-Robot Organisms: Reliability, Adaptability, Evolution, vol. 7. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-11692-6 CrossRefMATHGoogle Scholar
  14. 14.
    Mathews, G., Durrant-Whyte, H., Prokopenko, M.: Decentralized decision making for multiagent systems. In: Prokopenko, M. (ed.) Advances in Applied Self-organizing Systems. Advanced Information and Knowledge Processing, pp. 77–104. Springer, London (2008). doi: 10.1007/978-1-84628-982-8_5 CrossRefGoogle Scholar
  15. 15.
    Niemczyk, S., Geihs, K.: Adaptive run-time models for groups of autonomous robots. In: IEEE/ACM SEAMS 2015, pp. 127–133 (2015)Google Scholar
  16. 16.
    Saaty, T.L.: What is the analytic hierarchy process? In: Mitra, G., Greenberg, H.J., Lootsma, F.A., Rijkaert, M.J., Zimmermann, H.J. (eds.) Mathematical Models for Decision Support. NATO ASI Series. Springer, Heidelberg (1988). doi: 10.1007/978-3-642-83555-1_5 Google Scholar
  17. 17.
    Vromant, P., Weyns, D., Malek, S., Andersson, J.: On interacting control loops in self-adaptive systems. In: IEEE/ACM SEAMS 2011, pp. 202–207 (2011)Google Scholar
  18. 18.
    Weyns, D., Andersson, J.: On the challenges of self-adaptation in systems of systems. In: SESoS@ECOOP 2013. pp. 47–51 (2013)Google Scholar
  19. 19.
    Weyns, D., Malek, S., Andersson, J.: FORMS: unifying reference model for formal specification of distributed self-adaptive systems. TAAS 7(1), 8 (2012)CrossRefGoogle Scholar
  20. 20.
    Wohlin, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., Wesslén, A.: Experimentation in Software Engineering. Computer Science. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-29044-2 CrossRefMATHGoogle Scholar
  21. 21.
    Ye, D., Zhang, M., Sutanto, D.: Self-adaptation-based dynamic coalition formation in a distributed agent network: a mechanism and a brief survey. IEEE Trans. Parallel Distrib. Syst. 24(5), 1042–1051 (2013)CrossRefGoogle Scholar
  22. 22.
    Zambonelli, F., Bicocchi, N., Cabri, G., Leonardi, L., Puviani, M.: On self-adaptation, self-expression, and self-awareness in autonomic service component ensembles. In: SASOW, pp. 108–113 (2011)Google Scholar
  23. 23.
    Zhong, C., DeLoach, S.A.: Runtime models for automatic reorganization of multi-robot systems. In: IEEE/ACM SEAMS 2011, pp. 20–29 (2011)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Antonio Bucchiarone
    • 1
  • Martina De Sanctis
    • 1
  • Annapaola Marconi
    • 1
  1. 1.Fondazione Bruno KesslerTrentoItaly

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