Novel formulae for GSPN aggregation

J. Freiheit, A. Heindl
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引用次数: 5

Abstract

Stationary analysis of generalized stochastic Petri nets (GSPNs) often suffers from the state space explosion problem. Large reachability sets somorphic to continuous-time Markov chains - are not only expensive to generate, but related high-dimensional data structures also put excessive demands on numerical algorithms. In particular, sequences of transitions and alternative branches contribute multiplicatively to the size of the state space - if enabled concurrently. The paper examines under which circumstances such structures can be merged into a single timed transition while preserving the stationary token distributions in the embedding environment. For these aggregation steps on net level, novel formulae for the (locally) marking-dependent rates of the merged transition are developed, which solely rely on parameters of the aggregated subnet. These formulae bear a strong relation to flow equivalence. Examples throughout the paper demonstrate the gains both in drastically reduced state spaces and shortened processing times of the numerical analysis.
GSPN聚合的新公式
广义随机Petri网(GSPNs)的平稳分析经常遇到状态空间爆炸问题。大型可达集(与连续时间马尔可夫链同构)不仅生成成本高,而且相关的高维数据结构也对数值算法提出了过高的要求。特别是,转换序列和可选分支对状态空间的大小做出了成倍的贡献——如果并发启用的话。本文研究了在哪种情况下,这些结构可以合并到一个单一的定时转换中,同时在嵌入环境中保持平稳的令牌分布。对于这些网络级的聚合步骤,提出了新的(局部)标记依赖于合并转移率的公式,该公式仅依赖于聚合子网的参数。这些公式与流动等效关系密切。整篇论文的例子都证明了在大幅减少状态空间和缩短数值分析的处理时间方面的收益。
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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