Computationally efficient and numerically stable reliability bounds for repairable fault-tolerant systems
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The transient analysis of large continuous time Markov reliability models of repairable fault-tolerant systems is computationally expensive due to model stiffness. In this paper, we develop and analyze a method to compute bounds for a measure defined on a particular, but quite wide, class of continuous time Markov models, encompassing both exact and bounding continuous time Markov unreliability models of fault-tolerant systems. The method is numerically stable and computes the bounds with well-controlled and specifiable-in-advance error. Computational effort can be traded off with bounds accuracy. For a class of continuous time Markov models, class C’’, including typical failure/repair reliability models with exponential failure and repair time distributions and repair in every state with failed components, the method can yield reasonably tight bounds ay a very small computational cost. The method builds upon a recently proposed method for the transient analysis of continuous-time Markov models called regenerative randomization.
CitationCarrasco, J. Computationally efficient and numerically stable reliability bounds for repairable fault-tolerant systems. "IEEE transactions on computers", Març 2002, vol. 51, núm. 3, p. 254-268.
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