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非马尔可夫随机Petri网的分析方法及应用 被引量：3

Analysis Methods and Applications of Non-Markovian Stochastic Petri Nets
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摘要 Petri网是模型并行系统和分布式系统的一种强有效的形式化工具。它能够很好地刻画系统的动态行为、分析系统的性能。目前研究的大多数随机Petri网假定模型中所有变迁的实施时间呈指数分布,但是在许多实际系统中,变迁的实施时间呈确定性分布或一般性分布,这就需要研究非马尔可夫模型。文章主要讨论非马尔可夫随机Petri网的分析技术,即基于马尔可夫再生理论进行分析求解,并举例进行说明,在文章的最后进行了总结和展望。 Petri-Net is a quite valid formal tool for modeling parallel and distributed systems. It can describe dynamic behavior of systems in detail and evaluate performance of systems. At present, most developed models based on stochastic Petri Nets assume that all the firing times submit to exponential distributions. However, in many real systems, some firing times submit to deterministic or generic distributions. Hence there is a requirement for researching Non-Markovian models. In this paper, we mainly discuss an analysis method of Non-Markovian stochastic Petri Nets, which is based on Markov regenerative theory. After that, we give an example to illustrate this method. At the end of the paper, we summarize this analysis method and open up prospects for this area.
作者 林闯 李雅娟 刘雪宁
机构地区 清华大学计算机科学与技术系
出处 《系统仿真学报》 CAS CSCD 2003年第z1期71-75,共5页 Journal of System Simulation
基金 国家重点基础研究发展规划(973计划)项目(G1999032707) 国家自然科学基金(90104002和60173012) 国家高技术研究发展计划(863计划)课题(2001AA112080) 高等学校博士学科点专项科研基金项目(20020003027)。
关键词 非马尔可夫随机PETRI网 马尔可夫再生理论 抢占策略 分析方法 应用 non-markovian stochastic petri nets markov regenerative theory preemptive policies analysis methods applications
分类号 TP391.7 [自动化与计算机技术—计算机应用技术]
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参考文献24

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同被引文献26

  • 1唐俊,张明清,刘建峰.离散事件系统规范DEVS研究[J].计算机仿真,2004,21(6):62-64. 被引量：11
  • 2Rausand M, Hoyland A. System reliability theory : Models, statistical methods and applications[ M ]. Hoboken:John Wiley & Sons, 2004.
  • 3Cassandras C G, Lafortune S. Introduction to discrete event systems [ M ]. 2nd ed. New York : Springer Press,2008.
  • 4Leclercq E, Lefebvre D, Medhi S O. Petri nets design based on neural networks [ C ]//Proceedings of ESANN. Brnges, Belgium : [ s. n. ] ,2008:529-534.
  • 5Mehdi S O E, Leclercq E, Lefebvre D. Identification of stoehastie and deterministic stochastic Petri net models for reliability analysis [ J ]. Risk and Reliability, 2009,223 ( 1 ) : 13 - 26.
  • 6Lefebvre D, Leelereq E. Stochastic Petri net identification for the fault detection and isolation of discrete event systems[J]. IEEE Transactions on Systems Man and Cybernetics - Part A:Systems and Humans,2011,41 (2) :213-225.
  • 7Sara A T, Alla H. A control synthesis approach for time discrete event systems[J]. Mathematics and Computers in Simulation,2006,70 (5-6) :250-265.
  • 8Mellado E L. Analysis of discrete event systems by simulation of timed Petri net models [ J ]. Mathematics and Computers in Simulation ,2002,61 ( 1 ) :53-59.
  • 9Molloy M K. Performance analysis using stochastic Petri nets [J]. IEEE Trans on Computers,1982,C-31 (9) :913-917.
  • 10Mehdi S O E, Bekrar R, Messai N,et al. Design and identification of stochastic and deterministic stochastic Petri nets [ J ]. IEEE Transactions on Systems Man and Cybernetics - Part A:Systems and Humans,2012,42(4) :931-946.

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系统仿真学报
2003年 第z1期

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