Paper Info
Title
Uniformization and exponential transformation: Techniques for fast simulation of highly dependable non-Markovian systems
Abstract
The authors consider the estimation of system unreliability in highly dependable non-Markovian systems. They describe two alternative approaches to importance sampling for estimating transient reliability measures in such systems. One is based on the uniformization method of Monte Carlo simulation and the other uses an importance sampling distribution in which the failure times of components are sampled from the exponential distribution with rates higher than the original hazard rates. Implementation issues relevant to estimating system unreliability are discussed. Experimental results are given to illustrate the effectiveness of the proposed importance sampling techniques. Besides several small examples used for experimentation, a large example is used to illustrate the effectiveness of this technique for problems that are analytically intractable.<>
Year
DOI
Venue
1992
10.1109/FTCS.1992.243607
Boston, MA, USA
Keywords
Field
DocType
Monte Carlo methods,digital simulation,fault tolerant computing,Monte Carlo simulation,exponential transformation,fast simulation,highly dependable non-Markovian,highly dependable nonMarkovian systems,importance sampling,system unreliability,transient reliability measures
Applied mathematics,Uniformization (set theory),Importance sampling,Monte Carlo method,Exponential function,Markov process,Computer science,Acceleration,Exponential distribution,Reliability engineering,Buffer overflow
Conference
Citations 
PageRank 
References 
14
3.55
8
Authors
3
Name
Order
Citations
PageRank
Victor F. Nicola146884.45
Philip Heidelberger22331346.59
Perwez Shahabuddin31364181.65