Rare Event Simulation with Fully Automated Importance Splitting

TitleRare Event Simulation with Fully Automated Importance Splitting
Publication TypeBook Chapter
Year of Publication2015
AuthorsBudde, CE, D'Argenio, PR, Hermanns, H
EditorBeltrán, M, Knottenbelt, WJ, Bradley, JT
Book TitleComputer Performance Engineering - 12th European Workshop, {EPEW} 2015, Madrid, Spain, August 31 - September 1, 2015, Proceedings
Series TitleLecture Notes in Computer Science
Volume9272
Pagination275–290
PublisherSpringer
ISBN Number978-3-319-23266-9
AbstractProbabilistic model checking is a powerful tool for analysing probabilistic systems but it can only be efficiently applied to Markov models. Monte Carlo simulation provides an alternative for the generality of stochastic processes, but becomes infeasible if the value to estimate depends on the occurrence of rare events. To combat this problem, intelligent simulation strategies exist to lower the estimation variance and hence reduce the simulation time. Importance splitting is one such technique, but requires a guiding function typically defined in an ad hoc fashion by an expert in the field. We present an automatic derivation of the importance function from the model description. A prototypical tool was developed and tested on several Markov models, compared to analytically and numerically calculated results and to results of typical ad hoc importance functions, showing the feasibility and efficiency of this approach. The technique is easily adapted to general models like GSMPs.
URLhttp://dx.doi.org/10.1007/978-3-319-23267-6_18
DOI10.1007/978-3-319-23267-6_18
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