A Language-Based Approach to Autonomic Computing

  • Rocco De Nicola
  • Gianluigi Ferrari
  • Michele Loreti
  • Rosario Pugliese
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7542)

Abstract

SCEL is a new language specifically designed to model autonomic components and their interaction. It brings together various programming abstractions that permit to directly represent knowledge, behaviors and aggregations according to specific policies. It also supports naturally programming self-awareness, context-awareness, and adaptation. In this paper, we first present design principles, syntax and operational semantics of SCEL. Then, we show how a dialect can be defined by appropriately instantiating the features of the language we left open to deal with different application domains and use this dialect to model a simple, yet illustrative, example application. Finally, we demonstrate that adaptation can be naturally expressed in SCEL.

Keywords

Operational Semantic Service Component Label Transition System System Label Knowledge Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Hölzl, M., Rauschmayer, A., Wirsing, M.: Software Engineering for Ensembles. In: Wirsing, M., Banâtre, J.-P., Hölzl, M., Rauschmayer, A. (eds.) Software-Intensive Systems. LNCS, vol. 5380, pp. 45–63. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  2. 2.
    IBM: An architectural blueprint for autonomic computing. Technical report, 3rd edn. (June 2005)Google Scholar
  3. 3.
  4. 4.
    Project ASCENS (2010), http://www.ascens-ist.eu/
  5. 5.
    Wirsing, M., Hölzl, M., Tribastone, M., Zambonelli, F.: ASCENS: Engineering Autonomic Service-Component Ensembles. In: Beckert, B., de Boer, F., Bonsangue, M., Damiani, F. (eds.) FMCO 2011. LNCS, vol. 7542, pp. 1–24. Springer, Heidelberg (2012)Google Scholar
  6. 6.
    Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, I & II. Inf. Comput. 100(1), 1–77 (1992)MathSciNetCrossRefMATHGoogle Scholar
  7. 7.
    Plotkin, G.D.: A structural approach to operational semantics. J. Log. Algebr. Program. 60-61, 17–139 (2004)MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    De Nicola, R., Ferrari, G., Loreti, M., Pugliese, R.: Languages primitives for coordination, resource negotiation, and task description. ASCENS Deliverable D1.1 (September 2011), http://rap.dsi.unifi.it/scel/
  9. 9.
    De Nicola, R., Ferrari, G., Pugliese, R.: Klaim: A Kernel Language for Agents Interaction and Mobility. IEEE Trans. Software Eng. 24(5), 315–330 (1998)CrossRefGoogle Scholar
  10. 10.
    Gorla, D., Pugliese, R.: Dynamic management of capabilities in a network aware coordination language. J. Log. Algebr. Program. 78(8), 665–689 (2009)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    De Nicola, R., Gorla, D., Pugliese, R.: On the expressive power of klaim-based calculi. Theor. Comput. Sci. 356(3), 387–421 (2006)MathSciNetCrossRefMATHGoogle Scholar
  12. 12.
    Bruni, R., Corradini, A., Gadducci, F., Lluch Lafuente, A., Vandin, A.: A Conceptual Framework for Adaptation. In: de Lara, J., Zisman, A. (eds.) FASE 2012. LNCS, vol. 7212, pp. 240–254. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Hirschfeld, R., Costanza, P., Nierstrasz, O.: Context-oriented programming. Journal of Object Technology 7(3), 125–151 (2008)CrossRefGoogle Scholar
  14. 14.
    Want, R., Schooler, E., Jelinek, L., Jung, J., Dahle, D., Sengupta, U.: Ensemble computing: Opportunities and challenges. Intel Technology Journal 14(1), 118–141 (2010)Google Scholar
  15. 15.
    Hölzl, M., Wirsing, M.: Towards a System Model for Ensembles. In: Agha, G., Danvy, O., Meseguer, J. (eds.) Formal Modeling: Actors, Open Systems, Biological Systems. LNCS, vol. 7000, pp. 241–261. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  16. 16.
    Ashley-Rollman, M.P., Goldstein, S.C., Lee, P., Mowry, T.C., Pillai, P.: Meld: A declarative approach to programming ensembles. In: IROS, pp. 2794–2800. IEEE (2007)Google Scholar
  17. 17.
    Ashley-Rollman, M.P., Lee, P., Goldstein, S.C., Pillai, P., Campbell, J.D.: A Language for Large Ensembles of Independently Executing Nodes. In: Hill, P.M., Warren, D.S. (eds.) ICLP 2009. LNCS, vol. 5649, pp. 265–280. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  18. 18.
    Loo, B.T., Condie, T., Garofalakis, M., Gay, D.E., Hellerstein, J.M., Maniatis, P., Ramakrishnan, R., Roscoe, T., Stoica, I.: Declarative networking. Commun. ACM 52(11), 87–95 (2009)CrossRefGoogle Scholar
  19. 19.
    Baresi, L., Guinea, S., Tamburrelli, G.: Towards decentralized self-adaptive component-based systems. In: Proceedings of the 2008 International Workshop on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2008, pp. 57–64. ACM, New York (2008)CrossRefGoogle Scholar
  20. 20.
    Salvaneschi, G., Ghezzi, C., Pradella, M.: Context-oriented programming: A programming paradigm for autonomic systems. CoRR abs/1105.0069 (2011)Google Scholar
  21. 21.
    Igarashi, A., Pierce, B.C., Wadler, P.: Featherweight java: a minimal core calculus for Java and GJ. ACM Trans. Program. Lang. Syst. 23(3), 396–450 (2001)CrossRefGoogle Scholar
  22. 22.
    Hirschfeld, R., Igarashi, A., Masuhara, H.: ContextFJ: a minimal core calculus for context-oriented programming. In: Proceedings of the 10th International Workshop on Foundations of Aspect-Oriented Languages, FOAL 2011, pp. 19–23. ACM, New York (2011)Google Scholar
  23. 23.
    Clarke, D., Costanza, P., Tanter, E.: How should context-escaping closures proceed? In: Proc. of COP 2009, pp. 1:1–1:6. ACM, New York (2009)Google Scholar
  24. 24.
    Degano, P., Ferrari, G.-L., Galletta, L., Mezzetti, G.: Types for Coordinating Secure Behavioural Variations. In: Sirjani, M. (ed.) COORDINATION 2012. LNCS, vol. 7274, pp. 261–276. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  25. 25.
    Bhakti, M.A.C., Azween, A.: Formal modeling of an autonomic service oriented architecture. In: CSIT, vol. 5, pp. 23–29. IACSIT Press (2011)Google Scholar
  26. 26.
    Li, Z., Parashar, M.: Rudder: An agent-based infrastructure for autonomic composition of grid applications. Multiagent and Grid Systems 1(3) (2005) 183–195CrossRefMATHGoogle Scholar
  27. 27.
    Dong, X., Hariri, S., Xue, L., Chen, H., Zhang, M., Pavuluri, S., Rao, S.: Autonomia: an autonomic computing environment. In: IPCCC, pp. 61–68. IEEE (2003)Google Scholar
  28. 28.
    Mezzetti, N., Sangiorgi, D.: Towards a calculus for wireless systems. Electr. Notes Theor. Comput. Sci. 158, 331–353 (2006)CrossRefMATHGoogle Scholar
  29. 29.
    Singh, A., Ramakrishnan, C.R., Smolka, S.A.: A process calculus for mobile ad hoc networks. Sci. Comput. Program. 75(6), 440–469 (2010)MathSciNetCrossRefMATHGoogle Scholar
  30. 30.
    Banâtre, J.P., Radenac, Y., Fradet, P.: Chemical Specification of Autonomic Systems. In: IASSE, pp. 72–79. ISCA (2004)Google Scholar
  31. 31.
    Andrei, O., Kirchner, H.: A Higher-Order Graph Calculus for Autonomic Computing. In: Lipshteyn, M., Levit, V.E., McConnell, R.M. (eds.) Graph Theory, Computational Intelligence and Thought. LNCS, vol. 5420, pp. 15–26. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  32. 32.
    Bettini, L., De Nicola, R., Falassi, D., Lacoste, M., Loreti, M.: A Flexible and Modular Framework for Implementing Infrastructures for Global Computing. In: Kutvonen, L., Alonistioti, N. (eds.) DAIS 2005. LNCS, vol. 3543, pp. 181–193. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rocco De Nicola
    • 1
  • Gianluigi Ferrari
    • 2
  • Michele Loreti
    • 3
  • Rosario Pugliese
    • 3
  1. 1.Institute for Advanced Studies LuccaIMTItaly
  2. 2.Universitá degli Studi di PisaItaly
  3. 3.Universitá degli Studi di FirenzeItaly

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