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dc.contributor.authorCarrasco, Juan A.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.description.abstractThis paper targets the simulation of continuous-time Markov chain models of fault-tolerant systems with deferred repair. We start by stating sufficient conditions for a given importance sampling scheme to satisfy the bounded relative error property. Using those sufficient conditions, it is noted that many previously proposed importance sampling schemes such as failure biasing and balanced failure biasing satisfy that property. Then, we adapt the importance sampling schemes failure transition distance biasing and balanced failure transition distance biasing so as to develop new importance sampling schemes which can be implemented with moderate effort and at the same time can be proved to be more efficient for balanced systems than the simpler failure biasing and balanced failure biasing schemes. The increased efficiency for balanced and unbalanced systems of the new adapted importance sampling schemes is illustrated using examples.
dc.format.extent25 p.
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshFault-tolerant computing
dc.subject.lcshMarkov processes
dc.titleSimulation of steady-state availability models of fault-tolerant systems with deferred repair
dc.typeExternal research report
dc.subject.lemacTolerància als errors (Informàtica)
dc.subject.lemacMarkov, Processos de
dc.contributor.groupUniversitat Politècnica de Catalunya. QINE - Disseny de Baix Consum, Test, Verificació i Circuits Integrats de Seguretat
dc.rights.accessOpen Access

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