Knowledge Based Transactional Behavior

  • Saddek Bensalem
  • Marius Bozga
  • Doron Peled
  • Jean Quilbeuf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7857)


Component-based systems (including distributed programs and multiagent systems) involve a lot of coordination. This coordination is done in the background, and is transparent to the operation of the system. The reason for this overhead is the interplay between concurrency and non-deterministic choice: processes alternate between progressing independently and coordinating with other processes, where coordination can involve multiple choices of the participating components. This kind of interactions appeared as early as some of the main communication-based programming languages, where overhead effort often causes a restriction on the possible coordination. With the goal of enhancing the efficiency of coordination for component-based systems, we propose here a method for coordination-based on the precalculation of the knowledge of processes and coordination agents. This knowledge can be used to lift part of the communication or synchronization that appears in the background of the execution to support the interaction. Our knowledge-based method is orthogonal to the actual algorithms or primitives that are used to guarantee the synchronization: it only removes messages conveying information that knowledge can infer.


Cellular Automaton Global State Label Transition System Perfect Recall Dine Philosopher 
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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  1. 1.
    Bagrodia, R.: Process synchronization: Design and performance evaluation of distributed algorithms. IEEE Transactions on Software Engineering (TSE) 15(9), 1053–1065 (1989)CrossRefGoogle Scholar
  2. 2.
    Basu, A., Bensalem, S., Peled, D., Sifakis, J.: Priority scheduling of distributed systems based on model checking. Formal Methods in System Design 39, 229–245 (2011)zbMATHCrossRefGoogle Scholar
  3. 3.
    Basu, A., Bozga, M., Sifakis, J.: Modeling heterogeneous real-time components in BIP. In: Software Engineering and Formal Methods (SEFM), pp. 3–12 (2006)Google Scholar
  4. 4.
    Bensalem, S., Bozga, M., Quilbeuf, J., Sifakis, J.: Knowledge-based distributed conflict resolution for multiparty interactions and priorities. In: Giese, H., Rosu, G. (eds.) FMOODS/FORTE 2012. LNCS, vol. 7273, pp. 118–134. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Buckley, G.N., Silberschatz, A.: An effective implementation for the generalized input-output construct of CSP. ACM Trans. Program. Lang. Syst. 5, 223–235 (1983)zbMATHCrossRefGoogle Scholar
  6. 6.
    Chandy, K.M., Misra, J.: Parallel program design: a foundation. Addison-Wesley Longman Publishing Co., Inc., Boston (1988)zbMATHGoogle Scholar
  7. 7.
    Halpern, J.Y., Moses, Y.: Knowledge and common knowledge in a distributed environment. J. ACM 37, 549–587 (1990)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Hoare, C.A.R.: Communicating sequential processes. Commun. ACM 21, 666–677 (1978)zbMATHCrossRefGoogle Scholar
  9. 9.
    Joung, Y.-J., Smolka, S.A.: Strong interaction fairness via randomization. IEEE Trans. Parallel Distrib. Syst. 9(2), 137–149 (1998)CrossRefGoogle Scholar
  10. 10.
    Katz, G., Peled, D.: Code mutation in verification and automatic code correction. In: Esparza, J., Majumdar, R. (eds.) TACAS 2010. LNCS, vol. 6015, pp. 435–450. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Kumar, D.: An implementation of n-party synchronization using tokens. In: International Conference on Distributed Computing Systems (ICDCS), pp. 320–327. IEEE (1990)Google Scholar
  12. 12.
    Lehmann, D., Rabin, M.O.: On the advantages of free choice: a symmetric and fully distributed solution to the dining philosophers problem. In: Principles of Programming Languages, POPL (1981)Google Scholar
  13. 13.
    Der Meyden, R.V.: Common knowledge and update in finite environments. Information and Computation 140, 115–157 (1997)CrossRefGoogle Scholar
  14. 14.
    Pérez, J.A., Corchuelo, R., Toro, M.: An order-based algorithm for implementing multiparty synchronization. Concurrency and Computation: Practice and Experience 16(12), 1173–1206 (2004)CrossRefGoogle Scholar
  15. 15.
    Ricker, S.L., Rudie, K.: Know means no: Incorporating knowledge into discrete-event control systems. IEEE Trans. on Automatic Control 45(9), 1656–1668 (2000)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Saddek Bensalem
    • 1
  • Marius Bozga
    • 1
  • Doron Peled
    • 2
  • Jean Quilbeuf
    • 1
  1. 1.CNRS, VERIMAG UMR 5104UJF-Grenoble 1GrenobleFrance
  2. 2.Department of Computer ScienceBar Ilan UniversityRamat GanIsrael

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