Experimenting with the Static Slicing of Petri Nets

R. Davidrajuh
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引用次数: 3

Abstract

Petri net is a highly useful tool for modeling, simulation, and performance analysis of discrete event systems. However, the state spaces of the Petri net models of real-life discrete-event systems are enormous. Thus, model checking of these systems takes too much time, if it is possible at all. Therefore, static slicing of Petri nets is proposed in the literature to reduce a Petri net into a smaller size on which model checking becomes possible. However, this paper finds some fundamental problems in the idea of static slicing of Petri nets: 1) Most of the algorithms given in the literature for slicing do not work for real-life discrete-event systems. 2) The idea that the smaller the Petri net (obtained by slicing), the better for model checking is fundamentally wrong. As this paper shows, removal of places can be harmful as it can cause larger state spaces than the original ones. This paper proposes four hypotheses for devising newer slicing algorithms that can work on Petri net models of real-life systems too.
Petri网的静态切片实验
Petri网是一个非常有用的工具,用于离散事件系统的建模、仿真和性能分析。然而,实际离散事件系统的Petri网模型的状态空间是巨大的。因此,如果可能的话,这些系统的模型检查花费了太多的时间。因此,文献中提出了Petri网的静态切片,以将Petri网缩小到更小的尺寸,从而使模型检查成为可能。然而,本文发现了Petri网静态切片思想中的一些基本问题:1)文献中给出的大多数切片算法不适用于实际的离散事件系统。2) Petri网越小(通过切片获得)越适合模型检查的想法从根本上是错误的。正如本文所示,删除位置可能是有害的,因为它可能导致比原始状态空间更大的状态空间。本文提出了四个假设,用于设计新的切片算法,这些算法也可以在现实系统的Petri网模型上工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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