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Transient analysis of deterministic and stochastic Petri nets

  • Hoon Choi
  • Vidyadhar G. Kulkarni
  • Kishor S. Trivedi
Full Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 691)

Abstract

Deterministic and stochastic Petri nets (DSPNs) are recognized as a useful modeling technique because of their capability to represent constant delays which appear in many practical systems. If at most one deterministic transition is allowed to be enabled in each marking, the state probabilities of a DSPN can be obtained analytically rather than by simulation. We show that the continuous time stochastic process underlying the DSPN with this condition is a Markov regenerative process and develop a method for computing the transient (time dependent) behavior. We also provide a steady state solution method using Markov regenerative process theory and show that it is consistent with the method of Ajmone Marsan and Chiola.

Keywords

Transient Analysis Steady State Probability Firing Time Reachability Graph Deterministic Transition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Hoon Choi
    • 1
  • Vidyadhar G. Kulkarni
    • 3
  • Kishor S. Trivedi
    • 2
  1. 1.Department of Computer ScienceDuke UniversityDurhamUSA
  2. 2.Department of Electrical EngineeringDuke UniversityDurhamUSA
  3. 3.Department of Operations ResearchUniversity of North CarolinaChapel HillUSA

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