随机Petri网分析中马尔可夫更新理论与补充变量的形式关系

R. German, M. Telek
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引用次数: 22

摘要

本文主要利用马尔可夫更新理论和补充变量法研究了非马尔可夫随机Petri网。两种方法对同一系统提供了不同的分析描述。基于这些描述的数值算法得出了类似的结果。由于两者的确切关系尚不清楚,因此进行了平行研究。本文建立了具有一般抢占策略的马尔可夫再生随机Petri网在暂态和平稳情况下的这种形式关系。作为一个副产品,我们得到了一个拉普拉斯域的封闭解,它比以前已知的解更容易应用。从通信的一个例子是用于说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Formal relation of Markov renewal theory and supplementary variables in the analysis of stochastic Petri nets
Non-Markovian stochastic Petri nets have been investigated mainly by means of Markov renewal theory and by the method of supplementary variables. Both approaches provide different analytic descriptions of the same system. Numerical algorithms based on these descriptions lead to similar results. Parallel research effort resulted from the fact that an exact relationship of the two was not known. In this paper such a formal relationship is established for Markov regenerative stochastic Petri nets with general preemption policies in both the transient and stationary case. As a by-product, a closed form solution in Laplace domain is derived, which is easier to apply than previously known ones. An example from communications is used for illustrations.
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