CONCUR 1998: CONCUR'98 Concurrency Theory pp 389-404 | Cite as
Probabilistic resource failure in real-time process algebra
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Abstract
PACSR, a probabilistic extension of the real-time process algebra ACSR, is presented. The extension is built upon a novel treatment of the notion of a resource. In ACSR, resources are used to model contention in accessing physical devices. Here, resources are invested with the ability to fail and are associated with a probability of failure. The resulting formalism allows one to perform probabilistic analysis of real-time system specifications in the presence of resource failures. A probabilistic variant of Hennessy-Milner logic with until is presented. The logic features an until operator which is parameterized by both a probabilistic constraint and a regular expression over observable actions. This style of parameterization allows the application of probabilistic constraints to complex execution fragments. A model-checking algorithm for the proposed logic is also given. Finally, PACSR and the logic are illustrated with a telecommunications example.
Keywords
Model Check Temporal Logic Regular Expression Operational Semantic Probabilistic Constraint
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References
- 1.R. Alur, L. Jagadeesan, J. Kott, and J. V. Olnhausen. Model-checking of real-time systems: a telecommunications application. In Proceedings of the International Conference on Software Engineering, 1997.Google Scholar
- 2.J. Baeten, J. Bergstra, and S. Smolka. Axiomatizing probabilistic processes: ACP with generative probabilities. Information and Computation, 121(2):234–255, Sept. 1995.MATHMathSciNetCrossRefGoogle Scholar
- 3.C. Baier, E. Clarke, V. Hartonas-Garmhausen, M. Kwiatkowska, and M. Ryan. Symbolic model checking for probabilistic processes. In Proceedings of ICALP '97, volume 1256 of Lecture Notes in Computer Science, pages 430–440. Springer-Verlag, July 1997.Google Scholar
- 4.C. Baier and M. Kwiatkowska. Automatic verification of liveness properties of randomized systems (extended abstract). In Proceedings of the 14th Annual ACM Symposium on Principles of Distributed Computing, Santa Barbara, California, Aug. 1997.Google Scholar
- 5.H. Ben-Abdallah, D. Clarke, I. Lee, and O. Sokolsky. PARAGON: A Paradigm for the Specification, Verification, and Testing of Real-Time Systems. In IEEE Aerospace Conference, pages 469–488, Feb 1–8 1997.Google Scholar
- 6.A. Bianco and L. de Alfaro. Model checking of probabilistic and nondeterministic systems. In Proceedings Foundations of Software Techonology ans Theoretical Computer Science, volume 1026 of Lecture Notes in Computer Science, pages 499–513. Springer-Verlag, 1995.Google Scholar
- 7.E. Clarke and E. Emerson. Design and Synthesis of Synchronization Skeletons Using Branching Time Temporal Logic. LNCS 131, 1981.Google Scholar
- 8.E. Clarke, E. Emerson, and A. P. Sistla. Automatic verification of finite state concurrent systems using temporal logic specifications. ACM Trans. Prog. Lang. Syst., 8(2), 1986.Google Scholar
- 9.R. De Nicola and P. Vaandrager. Three logics for branching bisimulation. In Proceedngs of LICS '90. IEEE Computer Society Press, 1990.Google Scholar
- 10.A. Giacalone, C. Jou, and S. Smolka. Algebraic reasoning for probabilistic concurrent systems. In Proceedings of Working Conference on Programming Concepts and Methods, Sea of Gallilee, Israel, Apr. 1990. IFIP TC 2, North-Holland.Google Scholar
- 11.P. Halmos. Measure Theory. Springer Verlag, 1950.Google Scholar
- 12.H. Hansson. Time and Probability in Formal Design of Distributed Systems. PhD thesis, Department of Computer Systems, Uppsala University, 1991. DoCS 91/27.Google Scholar
- 13.H. Hansson and B. Jonsson. A logic for reasoning about time and probability. Formal Aspects of Computing, 6:512–535, 1994.MATHCrossRefGoogle Scholar
- 14.P. Iyer and M. Narasimha. ‘almost always’ and ‘definitely sometime’ are not enough: Probabilistic quantifiers and probabilistic model checking. Technical Report TR-96-16, Department of Computer Science, North Carolina State University, July 1996.Google Scholar
- 15.H. Karloff. Linear Programming. Progress in Theoretical Computer Science. Birkhauser, 1991.Google Scholar
- 16.J.-P. Katoen, R. Langerak, and D. Latella. Modeling systems by probabilistic process algebra: An event structures approach. In Proceedings of FORTE '92 — Fifth International Conference on Formal Description Techniques, pages 255–270, Oct. 1993.Google Scholar
- 17.I. Lee, P. Brémond-Grégoire, and R. Gerber. A process algebraic approach to the specification and analysis of resource-bound real-time systems. Proceedings of the IEEE, pages 158–171, Jan 1994.Google Scholar
- 18.R. Segala. Modelling and Verification of Randomized Distributed Real-Time Systems. PhD thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 1995.Google Scholar
- 19.R. Segala and N. Lynch. Probabilistic simulations for probabilistic processes. In B. Jonsson and J. Parrow, editors, Proceedings CONCUR 94, Uppsala, Sweden, volume 836 of Lecture Notes in Computer Science, pages 481–496. Springer-Verlag, 1994.Google Scholar
- 20.K. Seidel. Probabilistic CSP. PhD thesis, Oxford University, 1992.Google Scholar
- 21.C. Tofts. Processes with probabilities, priorities and time. Formal Aspects of Computing, 4:536–564, 1994.CrossRefGoogle Scholar
- 22.M. Vardi. Automatic verification of probabilistic concurrent finite-state programs. In Proceedings 26th Annual Symposium on Foundations of Computer Science, pages 327–338. IEEE, 1985.Google Scholar
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