Analysis of Stochastic Petri Net model with non-exponential distributions using a generalized Markov Renewal Process

Qun Jin, Yoshio Sugasawa, Koichiro Seya

Research output: Contribution to journalArticle

Abstract

Stochastic Petri Nets have been developed to model and analyze systems involving concurrent activities. However, the firing times of a Stochastic Petri Net model are always exponentially distributed. This paper presents an aggregate approach on how to analyze Stochastic Petri Net model with non-exponential distributions using a generalized Markov Renewal Process. Therefore, the modeling flexibility of Petri Net and the analyzing power of Markov Renewal Process are fully exploited. Moreover, an Abstract Partial Reachability Graph is introduced to simplify the Markov solution. Furthermore, the aggregate approach is applied to evaluate performance of a parallel operation system.

Original languageEnglish
Pages (from-to)933-939
Number of pages7
JournalMicroelectronics Reliability
Volume31
Issue number5
DOIs
Publication statusPublished - 1991
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Safety, Risk, Reliability and Quality
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Electrical and Electronic Engineering

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