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首页> 外文会议>Reliability and Maintainability Symposium, 2002. Proceedings. Annual >A path-based algorithm to evaluate asymptotic unavailability for large Markov models
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A path-based algorithm to evaluate asymptotic unavailability for large Markov models

机译：基于路径的大型Markov模型的渐近不可用性评估算法

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摘要

Markov chains are commonly used to study the dependability of complex systems. Nevertheless, the explosion of the number of states when the modeled system becomes too large is still a major problem. In such cases, reliability and availability cannot be calculated using conventional methods based on the construction of the state graph. One of the possible solutions to avoid this problem is to use only a local description of the system: the Markov chain is not actually constructed, but the knowledge of the rules which govern its evolution enable exploration of the state graph step by step. This idea already led to efficient algorithms for the computation of reliability. In this paper, we propose a method exploiting this path-based approach to evaluate the asymptotic unavailability of a system which is completely and quickly repairable. Then we show on a simple example that the more reliable the system, the better the approximation given by our method. Finally, we apply the presented algorithm to an electrical power system, much too large to enable the use of conventional methods.
机译：马尔可夫链通常用于研究复杂系统的可靠性。然而，当建模系统变得太大时，状态数量的爆炸仍然是一个主要问题。在这种情况下，无法基于状态图的构造使用常规方法来计算可靠性和可用性。避免此问题的可能解决方案之一是仅使用系统的本地描述：马尔可夫链实际上并未构建，但是掌握控制其演化的规则的知识使您可以逐步探索状态图。这个想法已经导致了用于可靠性计算的高效算法。在本文中，我们提出了一种利用这种基于路径的方法来评估可完全且快速修复的系统的渐近不可用性的方法。然后，我们在一个简单的示例上表明，系统越可靠，我们的方法给出的近似值越好。最后，我们将提出的算法应用于电力系统，该系统太大而无法使用常规方法。

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