A New Approach to the Evaluation of Non Markovian Stochastic Petri Nets

  • Serge Haddad
  • Lynda Mokdad
  • Patrice Moreaux
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4024)


In this work, we address the problem of transient and steady-state analysis of a stochastic Petri net which includes non Markovian distributions with a finite support but without any additional constraint. Rather than computing an approximate distribution of the model (as done in previous methods), we develop an exact analysis of an approximate model. The design of this method leads to a uniform handling of the computation of the transient and steady state behaviour of the model. This method is an adaptation of a former one developed by the same authors for general stochastic processes (which was shown to be more robust than alternative techniques). Using Petri nets as the modelling formalism enables us to express the behaviour of the approximate process by tensorial expressions. Such a representation yields significant savings w.r.t. time and space complexity.


Probability Vector Probabilistic Choice Continuous Time Markov Chain Discrete Time Markov Chain Reachability Graph 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Serge Haddad
    • 1
  • Lynda Mokdad
    • 1
  • Patrice Moreaux
    • 2
  1. 1.LAMSADE, UMR CNRS 7024Universit Paris DauphinePARISFrance
  2. 2.LISTIC, ESIAUniversit de SavoieANNECYFrance

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