Rules and Implementation of Converting Stochastic Petri Net Model to Markov Chain

Stochastic Petri net is a kind of tool for system design and analysis, and can be used to qualitatively and quantitatively analyze system. In order to effectively use stochastic Petri net for performance quantitative analysis, according to the algorithm of converting stochastic Petri net model to isomorphic Markov chain, this paper summarizes and implements conversion rules. By introducing evolution rules and merger rules in the process of transition firing, the conversion rules transform stochastic Petri net model into Markov chain. A number of performance indicators of stochastic Petri net model can be quantitatively analyzed using the obtained Markov chain. The experimental results confirm the validity and feasibility of the conversion rules.