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Approximate closed-form aggregation of a fork-join structure in generalised stochastic petri nets

机译:广义随机Petri网中fork-join结构的近似闭合形式聚合

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In this paper an aggregation technique for generalised stochastic Petri nets (GSPNs) possessing synchronised parallel structures is presented. Parallel processes featuring synchronisation constraints commonly occur in fields such as product assembly and computer process communications, however their existence in closed networks severely complicates analysis. This paper details the derivation of computationally-simple closed-form expressions which permit the aggregation of a GSPN subnet featuring a fork-join structure. The aggregation expressions presented in this paper do not require the generation of the underlying continuous time Markov chain of the original net, and do not follow an iterative procedure. The resulting aggregated GSPN accurately approximates the stationary token distribution behaviour of the original net, and this is shown by the analysis of a number of example GSPNs.
机译:本文提出了一种具有同步并行结构的广义随机Petri网(GSPN)的聚合技术。具有同步约束的并行过程通常发生在诸如产品组装和计算机过程通信之类的领域,但是它们在封闭网络中的存在使分析变得更加复杂。本文详细介绍了计算简单的封闭式表达式的推导,这些表达式允许聚合具有叉连接结构的GSPN子网。本文中提出的聚合表达式不需要生成原始网络的基础连续时间马尔可夫链,并且不需要遵循迭代过程。生成的汇总GSPN可以准确地近似原始网络的固定令牌分发行为,这通过对多个示例GSPN的分析得以显示。

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