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Iterative decomposition and aggregation of Stochastic marked graph Petri nets

  • Yao Li
  • C. Murray Woodside
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 674)

Abstract

This paper addresses the problem of state explosion and computational complexity in solving marked graph Stochastic Petri Nets (SPNs). We first develop a simple and powerful Petri Nets (PNs) reduction technique that reduces the size of a marked graph PN. Then we propose an iterative delay equivalent reduction technique to solve the reduced SPN. This method iteratively tunes two or more partly aggregated auxiliary SPNs until they are approximately delay equivalent to the original SPN. It avoids the direct solution of the original SPN. In our experience the iteration usually converges and the accuracy is usually better than 5%, though there are exceptional cases. The technique is a step towards approximating more general SPNs.

Keywords

(Generalized) Stochastic Petri nets Markov chain marked graph PN reduction and delay equivalent aggregation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Yao Li
    • 1
  • C. Murray Woodside
    • 1
  1. 1.Telecommunications Research Institute of Ontario Department of Systems and Computer EngineeringCarleton UniversityOttawaCanada

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