随机Petri网模型到马尔可夫链的转换规则与实现

随机Petri网是一种系统设计和分析工具,它可以对系统进行定性分析和定量分析。为了有效利用随机Petri网进行性能的定量分析,根据随机Petri网模型转换为马尔可夫链的算法,总结并实现了它们之间的转换规则。该转换规则在变迁实施的过程中引入演变规则和合并规则,将随机Petri网模型转换为马尔可夫链。可以利用产生的马尔可夫链对随机Petri网模型的多项性能指标进行定量分析。实验结果表明,转换规则是正确、可行的。

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.