Title :
Quick estimation of rare events in stochastic networks
Author :
Lieber, Dmitrii ; Rubinstein, Reuven Y. ; Elmakis, David
Author_Institution :
Technion-Israel Inst. of Technol., Haifa, Israel
fDate :
6/1/1997 12:00:00 AM
Abstract :
This paper presents a method for fast estimation of probabilities of rare events in stochastic networks, with a particular emphasis on coherent reliability systems. The method is based on the concepts of likelihood-ratios (LR), change of probability measure and the bottleneck-cut in the network. Both polynomial and exponential-time Monte Carlo estimators are defined, and conditions under which the time complexity of the proposed LR estimators is bounded by a polynomial are discussed. The accuracy of the method depends only on the size (cardinality) of the bottleneck-cut, not on the topology and actual size of the network. Supporting numerical results are presented, with the cardinality of the bottleneck-cut ⩽20
Keywords :
Monte Carlo methods; failure analysis; probability; reliability theory; sensitivity analysis; stochastic processes; bottleneck-cut; cardinality; coherent reliability systems; exponential-time Monte Carlo estimators; likelihood-ratios; polynomial Monte Carlo estimators; polynomial bounding; probability measure; rare event probability estimation; reliability; stochastic networks; Analytical models; Approximation algorithms; Discrete event simulation; Intelligent networks; Monte Carlo methods; Network topology; Polynomials; Sensitivity analysis; Stochastic processes; Stochastic systems;
Journal_Title :
Reliability, IEEE Transactions on
