Markov Regenerative Stochastic Petri Nets to Model and Evaluate Phased Mission Systems Dependability
Markov Regenerative Stochastic Petri Nets to Model and Evaluate Phased Mission Systems Dependability
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DOI：
10.1109/tc.2001.970572
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发表时间：
2001-12
期刊：
影响因子：
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通讯作者：
I. Mura;A. Bondavalli
中科院分区：
文献类型：
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作者：
I. Mura;A. Bondavalli
研究了基于模型的多阶段使命系统可靠性瞬态分析。文献中的研究表明，多相系统的几个方面提出了具有挑战性的问题，可靠性评估方法和工具。为了攻击的弱点，最先进的，我们提出了一种建模方法，利用马尔可夫再生随机Petri网模型的类的权力。通过利用文献中的马尔可夫再生过程的分析技术，我们得到了一个分析的解决方案，具有较低的计算复杂性，基本上由每个阶段内的系统的单独分析的成本占主导地位。最后，解析解的存在使我们能够推导出可靠性措施的灵敏度函数，从而为可靠性工程师提供了研究分阶段使命系统的额外手段。
This study deals with model-based dependability transient analysis of phased mission systems. A review of the studies in the literature showed that several aspects of multiphased systems pose challenging problems to the dependability evaluation methods and tools. To attack the weak points of the state-of-the-art we propose a modeling methodology that exploits the power of the class of Markov regenerative stochastic Petri net models. By exploiting the techniques available in the literature for the analysis of the Markov Regenerative Processes, we obtain an analytical solution technique with a low computational complexity, basically dominated by the cost of the separate analysis of the system inside each phase. Last, the existence of analytical solutions allows us to derive the sensitivity functions of the dependability measures, thus providing the dependability engineer with additional means for the study of phased mission systems.