Non-regenerative stochastic Petri nets: Modeling and analysis

Qun Jin, Yoneo Yano, Yoshio Sugasawa

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We develop a new class of stochastic Petri net: non-regenerative stochastic Petri net (NRSPN), which allows the firing time of its transitions with arbitrary distributions, and can automatically generate a bounded reachability graph that is equivalent to a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. Thus, it can model and analyze behavior of a system whose states include some non-regeneration points. We show how to model a system by the NRSPN, and how to obtain numerical solutions for the NRSPN model. The probabilistic behavior of the modeled system can be clarified with the reliability measures such as the steady-state probability, the expected numbers of visits to each state per unit time, availability, unavailability and mean time between system failure. Finally, to demonstrate the modeling ability and analysis power of the NRSPN model, we present an example for a fault-tolerant system using the NRSPN and give numerical results for specific distributions.

Original languageEnglish
Pages (from-to)1781-1790
Number of pages10
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE79-A
Issue number11
Publication statusPublished - 1996
Externally publishedYes

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Keywords

  • Behavior modeling
  • Fault tolerance
  • Markov renewal process
  • Reliability analysis
  • Stochastic Petri nets

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Information Systems

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