Dissemination of Reconfiguration Policies on Mesh Networks

  • François Fouquet
  • Erwan Daubert
  • Noël Plouzeau
  • Olivier Barais
  • Johann Bourcier
  • Jean-Marc Jézéquel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7272)

Abstract

Component-based platforms are widely used to develop and deploy distributed pervasive system that exhibit a high degree of dynamicity, concurrency, distribution, heterogeneity, and volatility. This paper deals with the problem of ensuring safe yet efficient dynamic adaptation in a distributed and volatile environment. Most current platforms provide capabilities for dynamic local adaptation to adapt these systems to their evolving execution context, but are still limited in their ability to handle distributed adaptations. Thus, a remaining challenge is to safely propagate reconfiguration policies of component-based systems to ensure consistency of the architecture configuration models over a dynamic and distributed system. In this paper we implement a specific algorithm relying on the models at runtime paradigm to manage platform independent models of the current system architecture and its deployed configuration, and to propagate reconfiguration policies. We evaluate a combination of gossip-based algorithms and vector clock techniques that are able to propagate these policies safely in order to preserve consistency of architecture configuration models among all computation nodes of the system. This evaluation is done with a test-bed system running on a large size grid network.

References

  1. 1.
    Almeida, P.S., Baquero, C., Fonte, V.: Interval Tree Clocks: A Logical Clock for Dynamic Systems. In: Baker, T.P., Bui, A., Tixeuil, S. (eds.) OPODIS 2008. LNCS, vol. 5401, pp. 259–274. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  2. 2.
    Baldoni, R., Raynal, M., Dis, U.R.L.S.: Fundamentals of distributed computing: A practical tour of vector clock systems. IEEE Distributed Systems Online 3(2), 1–18 (2002)Google Scholar
  3. 3.
    Blair, G.S., Bencomo, N., France, R.B.: Models@runtime. IEEE Computer 42(10), 22–27 (2009)CrossRefGoogle Scholar
  4. 4.
    Bruneton, E., Coupaye, T., Leclercq, M., Quéma, V., Stefani, J.-B.: The fractal component model and its support in java: Experiences with auto-adaptive and reconfigurable systems. Softw. Pract. Exper. 36(11-12), 1257–1284 (2006)CrossRefGoogle Scholar
  5. 5.
    Cheng, C., Riley, R., Kumar, S.P.R., Garcia-Luna-Aceves, J.J.: A loop-free extended bellman-ford routing protocol without bouncing effect. SIGCOMM Comput. Commun. Rev. 19, 224–236 (1989)CrossRefGoogle Scholar
  6. 6.
    Eugster, P.T., Guerraoui, R., Kermarrec, A.M., Massoulié, L.: From epidemics to distributed computing. IEEE Computer 37(5), 60–67 (2004)CrossRefGoogle Scholar
  7. 7.
    Fidge, C.J.: Timestamps in message-passing systems that preserve the partial ordering. In: Proceedings of the 11th ACSC, vol. 10, pp. 56–66 (1988)Google Scholar
  8. 8.
    Johnson, R., Woolf, B.: The Type Object Pattern (1997)Google Scholar
  9. 9.
    Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing. Computer 36(1), 41–50 (2003)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Communications of the ACM 21(7), 558–565 (1978)MATHCrossRefGoogle Scholar
  11. 11.
    Leitão, J., Pereira, J., Rodrigues, L.: Gossip-based broadcast. In: Handbook of Peer-to-Peer Networking, pp. 831–860 (2010)Google Scholar
  12. 12.
    Lin, S., Taïani, F., Blair, G.S.: Facilitating Gossip Programming with the GossipKit Framework. In: Meier, R., Terzis, S. (eds.) DAIS 2008. LNCS, vol. 5053, pp. 238–252. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Mattern, F.: Virtual time and global states of distributed systems. Parallel and Distributed Algorithms, 215–226 (1989)Google Scholar
  14. 14.
    Morin, B., Barais, O., Jézéquel, J.-M., Fleurey, F., Solberg, A.: Models@ run.time to support dynamic adaptation. Computer 42(10), 44–51 (2009)CrossRefGoogle Scholar
  15. 15.
    Raj, G.S., Binod, P.G., Babo, K., Palkovic, R.: Implementing service-oriented architecture (soa) with the java ee 5 sdk. Sun Microsystems, revision 3 (2006)Google Scholar
  16. 16.
    Schollmeier, R.: A definition of peer-to-peer networking for the classification of peer-to-peer architectures and applications. In: Proceedings of the First International Conference on Peer-to-Peer Computing, pp. 101–102. IEEE (2001)Google Scholar
  17. 17.
    Sykes, D., Magee, J., Kramer, J.: Flashmob: distributed adaptive self-assembly. In: Proceeding of the 6th SEAMS, pp. 100–109. ACM (2011)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • François Fouquet
    • 1
  • Erwan Daubert
    • 1
  • Noël Plouzeau
    • 1
  • Olivier Barais
    • 1
  • Johann Bourcier
    • 1
  • Jean-Marc Jézéquel
    • 1
  1. 1.University of Rennes 1, IRISA, INRIA Centre RennesRennesFrance

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