Markov regenerative stochastic Petri nets

TitleMarkov regenerative stochastic Petri nets
Publication TypeJournal Article
Year of Publication1994
AuthorsH Choi, VG Kulkarni, and KS Trivedi
JournalPerformance Evaluation
Volume20
Issue1-3
Start Page337
Pagination337 - 357
Date Published01/1994
Abstract

Stochastic Petri nets of various types (SPN, GSPN, ESPN, DSPN etc.) are recognized as useful modeling tools for analyzing the performance and reliability of systems. The analysis of such Petri nets proceeds by utilizing the underlying continuous-time stochastic processes - continuous-time Markov chains for SPN and GSPN, semi-Markov processes for a subset of ESPNs and Markov regenerative processes for DSPN. In this paper, we introduce a new class of stochastic Petri nets, called Markov Regenerative Stochastic Petri Nets (MRSPNs), that can be analyzed by means of Markov regenerative processes and constitutes a true generalization of all the above classes. The MRSPNs allow immediate transitions, exponentially distributed timed transitions and generally distributed timed transitions. With a restriction that at most one generally distributed timed transition be enabled in each marking, the transient and steady state analysis of MRSPNs can be carried out analytically-numerically rather than by simulation. Equations for the solution of MRSPNs are developed in this paper, and are applied to an example. © 1994.

DOI10.1016/0166-5316(94)90021-3
Short TitlePerformance Evaluation