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Probabilistic KLAIM

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Coordination Models and Languages (COORDINATION 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2949))

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Abstract

We introduce a probabilistic extension of KLAIM, where the behaviour of networks and individual nodes is determined by a probabilistic scheduler for processes and probabilistic allocation environments which describe the logical neighbourhood of each node. The resulting language has two variants which are modelled respectively as discrete and continuous time Markov processes. We suggest that Poisson processes are a natural probabilistic model for the coordination of discrete processes asynchronously communicating in continuous time and we use them to define the operational semantics of the continuous time variant. This framework allows for the implementation of networks with independent clocks on each site.

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References

  1. De Nicola, R., Ferrari, G., Pugliese, R.: KLAIM: A kernel language for agents interaction and mobility. IEEE Transactions on Software Engineering 24, 315–330 (1998)

    Article  Google Scholar 

  2. Norris, J.: Markov Chains. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge (1997)

    Book  MATH  Google Scholar 

  3. Bause, F., Kritzinger, P.S.: Stochastic Petri Nets – An Introduction to the Theory, 2nd edn. Vieweg Verlag (2002)

    Google Scholar 

  4. Tijms, H.C.: Stochastic Models – An Algorithmic Approach. John Wiley & Sons, Chichester (1994)

    MATH  Google Scholar 

  5. Di Pierro, A., Hankin, C., Wiklicky, H.: Analysing the propagation of computer viruses. Journal of Functional Programming (2003) (submitted)

    Google Scholar 

  6. Giacalone, A., Jou, C.C., Smolka, S.: Algebraic reasoning for probabilistic concurrent systems. In: Proceedings of the IFIP WG 2.2/2.3 Working Conference on Programming Concepts and Methods, pp. 443–458. North-Holland, Amsterdam (1990)

    Google Scholar 

  7. Jonsson, B., Yi, W., Larsen, K.: 11. In: Probabilistic Extentions of Process Algebras, pp. 685–710. Elsevier Science, Amsterdam (2001); see [17]

    Google Scholar 

  8. Di Pierro, A., Wiklicky, H.: Quantitative observables and averages in Probabilistic Concurrent Constraint Programming. In: Apt, K.R., et al. (eds.) Compulog Net WS 1999. LNCS (LNAI), vol. 1865, p. 212. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  9. Hillston, J.: PEPA: Performance enhanced process algebra. Technical Report CSR-24-93, University of Edinburgh, Edinburgh, Scotland (1993)

    Google Scholar 

  10. Priami, C.: Stochastic π-calculus. Computer Journal 38, 578–589 (1995)

    Article  Google Scholar 

  11. Hillston, J.: A Compositional Approach to Performance Modelling. Cambridge University Press, Cambridge (1996)

    Book  MATH  Google Scholar 

  12. Bernardo, M., Gorrieri, R.: A tutorial on EMPA: A theory of concurrent processes with nondeterminism, priorities, probabilities and time. Technical Report UBLCS-96-17, Department of Computer Science, University of Bologna (1997)

    Google Scholar 

  13. Kwiatkowska, M., Norman, G., Parker, D.: Probabilistic symbolic model checking with PRISM: A hybrid approach. In: Katoen, J.-P., Stevens, P. (eds.) TACAS 2002. LNCS, vol. 2280, pp. 52–66. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  14. de Alfaro, L.: Formal Verification of Probabilistic Systems. PhD thesis, Stanford University, Department of Computer Science (1998)

    Google Scholar 

  15. Di Pierro, A., Hankin, C., Wiklicky, H.: Approximate Non-Interference. Journal of Computer Security 12, 37–81 (2004)

    Article  Google Scholar 

  16. Aldini, A., Bravetti, M., Gorrieri, R.: A process algebraic approach for the analysis of probabilistic non-interference. Journal of Computer Security (2004)

    Google Scholar 

  17. Bergstra, J., Ponse, A., Smolka, S. (eds.): Handbook of Process Algebra. Elsevier Science, Amsterdam (2001)

    MATH  Google Scholar 

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Di Pierro, A., Hankin, C., Wiklicky, H. (2004). Probabilistic KLAIM. In: De Nicola, R., Ferrari, GL., Meredith, G. (eds) Coordination Models and Languages. COORDINATION 2004. Lecture Notes in Computer Science, vol 2949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24634-3_11

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  • DOI: https://doi.org/10.1007/978-3-540-24634-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21044-3

  • Online ISBN: 978-3-540-24634-3

  • eBook Packages: Springer Book Archive

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