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

Qun Jin; Yoshio Sugasawa; Koichiro Seya

doi:10.1016/0026-2714(91)90038-9

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 journal › Article › peer-review

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 language	English
Pages (from-to)	933-939
Number of pages	7
Journal	Microelectronics Reliability
Volume	31
Issue number	5
DOIs	https://doi.org/10.1016/0026-2714(91)90038-9
Publication status	Published - 1991
Externally published	Yes

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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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.",

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year = "1991",

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PY - 1991

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N2 - 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.

AB - 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.

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SN - 0026-2714

IS - 5

ER -

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

Abstract

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