An Approach to Performance Equivalent Simplification and Analysis of Stochastic Petri Nets

Stochastic Petri Net (SPN) are a powerful modeling and analyzing tool for system performance evaluation.But the problem of state space's explosion of SPN limits its ability to analyze complex and large scale systems.So it is more feasible to simplify SPN model on the basis of performance equivalence before analyzing it.In this paper,the authors define a class of SPN Elementary SPN (ESPN) which is composed of four elementary subnets including sequence subnet,parallel subnet,choice subnet and iteration subnet,and propose a group of performance equivalence formulas for the four elementary subnets,as well as a method of performance equivalence simplification and analysis for ESPN with linear time complexity.In addition,two transforming rules are put forward to transform non elementary subnets into combined elementary subnets such that the proposed algorithm can be used in analysis of more general SPN.