Techniques for fast simulation of models of highly dependable systems

Dept. of Electr. Eng., Twente Univ., Enschede
IEEE Transactions on Reliability (Impact Factor: 2.29). 10/2001; DOI: 10.1109/24.974122
Source: IEEE Xplore

ABSTRACT 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

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