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Joint International Workshop von Process Algebra and Probabilistic Methods, Performance Modeling and Verification

PAPM-PROBMIV 2001: Process Algebra and Probabilistic Methods. Performance Modelling and Verification pp 184–199Cite as

Quantifying the Dynamic Behavior of Process Algebras

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2165))

Abstract

The paper introduces a new approach to define process algebras with quantified transitions. A mathematical model is introduced which allows the definition of various classes of process algebras including the well known models of untimed, probabilistic and stochastic process algebras. For this general mathematical model a bisimulation equivalence is defined and it is shown that the equivalence is a congruence according to the operations of the algebra. By means of some examples it is shown that the proposed approach allows the definition of new classes of process algebras like process algebras over the max/plus or min/plus semirings.

This research is partially supported by DFG, SFB 358

This research is partially supported by DFG, SFB 559

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References

  1. R. Agrawal, F. Baccelli, and R. Rajan. An algebra for queueing networks with time varying service. Research Report 3435, INRIA, 1998.

    Google Scholar 

  2. F. Baccelli, G. Cohen, G. Olsder, and J. Quadrat. Synchronization and Linearity. John Wiley and Sons, 1992.

    Google Scholar 

  3. F. Baccelli, B. Gaujal, and D. Simon. Analysis of preemptive periodic real time systems using the (max,plus) algebra. Research Report 3778, INRIA, 1999.

    Google Scholar 

  4. F. Baccelli and D. Hong. TCP is (max/+) linear. In Proc. SIGCOM 2000. ACM, 2000.

    Google Scholar 

  5. M. Bernado and R. Gorrieri. A tuturial of EMPA: A theory of concurrent processes with nondeterminism, priorities, probabilities and time. Theoretical Computer Science, 202:1–54, 1998.

    Article  MathSciNet  Google Scholar 

  6. D. P. Bertsekas and J. N. Tsitsiklis. Parallel and distributed computation. Prentice Hall, 1989.

    Google Scholar 

  7. P. Buchholz. Die strukturierte Analyse Markovscher Modelle (in German). IFB 282. Springer, 1991.

    Google Scholar 

  8. P. Buchholz. Markovian process algebra: composition and equivalence. In [17].

    Google Scholar 

  9. P. Buchholz. Bisimulation for automata with transition costs. submitted, 2000.

    Google Scholar 

  10. C. S. Chang. Performance guarantess in communication networks. Springer, 1999.

    Google Scholar 

  11. R. Cleaveland, J. Parrow, and B. Steffen. The concurrency workbench: a semantics based tool for the verification of concurrent systems. ACM Transactions on Programming Languages and Systems, 15(1):36–72, 1993.

    Article  Google Scholar 

  12. P. R. D’Argenio, H. Hermanns, and J. P. Katoen. On generative parallel composition. In Proc. ProbMiv 98, Electronic Notes on Theor. Computer Sc., 21, 1999.

    Google Scholar 

  13. D. Gross and D. Miller. The randomization technique as a modeling tool and solution procedure for transient Markov processes. Operations Research, 32(2):926–944, 1984.

    Article  MathSciNet  Google Scholar 

  14. H. Hansson. Time and probability for the formal design of distributed systems. Phd thesis, University of Uppsala, 1991.

    Google Scholar 

  15. H. Hermanns, U. Herzog, and V. Mertsiotakis. Stochastic process algebras — between LOTOS and Markov chains. Computer Networks and ISDN Systems, 30(9/10):901–924, 1998.

    Article  Google Scholar 

  16. H. Hermanns and M. Rettelbach. Syntax, semantics, equivalences, and axioms for MTIPP. In [17]

    Google Scholar 

  17. U. Herzog and M. Rettelbach, eds. Proc. 2nd Work. Process Algebras and Performance Modelling Arbeitsberichte IMMD, Univ. Erlangen, Germany, No. 27, 1994.

    Google Scholar 

  18. J. Hillston. The nature of synchronisation. In [17].

    Google Scholar 

  19. J. Hillston. A compositional approach for performance modelling. Phd thesis, University of Edinburgh, Dep. of Comp. Sc., 1994.

    Google Scholar 

  20. J. Hillston. Compositional Markovian modelling using a process algebra. In W. J. Stewart, editor, Computations with Markov Chains, pages 177–196. Kluwer, 1995.

    Google Scholar 

  21. C. Hoare. Communicating sequential processes. Prentice Hall, 1985.

    Google Scholar 

  22. K. Larsen and A. Skou. Bisimulation through probabilistic testing. Information and Computation, 94: 1–28, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  23. R. Milner. Communication and concurrency. Prentice Hall, 1989.

    Google Scholar 

  24. D. Park. Concurrency and automata on infinite sequences. In Proc. 5th GI Conference on Theoretical Computer Science, pages 167–183. Springer LNCS 104, 1981.

    Google Scholar 

  25. R. van Glabbek, S. Smolka, B. Steffen, and C. Tofts. Reactive, generative and stratified models for probabilistic processes. In Proc. LICS’90, 1990.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Fakultät für Informatik, TU Dresden, D-01062, Dresden, Germany

    Peter Buchholz

  2. Informatik IV, Universität Dortmund, D-44221, Dortmund, Germany

    Peter Kemper

Authors
  1. Peter Buchholz
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  2. Peter Kemper
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Editor information

Editors and Affiliations

  1. Dept. of Electr. and Computer Science, University of California at Berkeley, 479 Cory Hall, Berkeley, CA94720-1770, USA

    Luca de Alfaro

  2. Laboratory for Foundations of Computer Science, The University of Edinburgh, Edinburgh, EH9 3JZ, UK

    Stephen Gilmore

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© 2001 Springer-Verlag Berlin Heidelberg

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Buchholz, P., Kemper, P. (2001). Quantifying the Dynamic Behavior of Process Algebras. In: de Alfaro, L., Gilmore, S. (eds) Process Algebra and Probabilistic Methods. Performance Modelling and Verification. PAPM-PROBMIV 2001. Lecture Notes in Computer Science, vol 2165. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44804-7_12

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  • DOI: https://doi.org/10.1007/3-540-44804-7_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42556-4

  • Online ISBN: 978-3-540-44804-4

  • eBook Packages: Springer Book Archive

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