Simulation of transient performance measures for stiff markov chains

We consider the simulation of transient performance measures of high reliable fault-tolerant computer systems. The most widely used mathematical tools to model the behavior of these systems are Markov processes. Here, we deal basically with the simulation of the mean time to failure (MTTF) and the r...

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Veröffentlicht in:	R.A.I.R.O. Recherche opérationnelle 2000-10, Vol.34 (4), p.385-396
1. Verfasser:	Nasroallah, Abdelaziz
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Sprache:	eng
Schlagworte:	Monte-Carlo simulation performance measures Reliability stiff Markovian models variance reduction
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description	We consider the simulation of transient performance measures of high reliable fault-tolerant computer systems. The most widely used mathematical tools to model the behavior of these systems are Markov processes. Here, we deal basically with the simulation of the mean time to failure (MTTF) and the reliability, R(t), of the system at time t. Some variance reduction techniques are used to reduce the simulation time. We will combine two of these techniques: Importance Sampling and Conditioning Technique. The resulting hybrid algorithm performs significant reduction of simulation time and gives stables estimations.
doi_str_mv	10.1051/ro:2000120
format	Article
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subjects	Monte-Carlo simulation performance measures Reliability stiff Markovian models variance reduction
title	Simulation of transient performance measures for stiff markov chains
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