Techniques for the Fast Simulation of Models of Highly dependable Systems

V.F. Nicola, Perwez Shahabuddin, Marvin K. Nakayama

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    With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable systems
    Original languageUndefined
    Pages (from-to)246-264
    Number of pages19
    JournalIEEE transactions on reliability
    Issue number03
    Publication statusPublished - 2001


    • Simulation
    • transient dependability measure
    • steady-state dependability measure
    • METIS-200966
    • IR-42280
    • Markov Chain
    • Importance sampling
    • Highly dependable system

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