Title
Adaptive state- dependent importance sampling simulation of markovian queueing networks
Abstract
In this paper, a method is presented for the efficient estimation of rare-event (buffer overflow) probabilities in queueing networks using importance sampling. Unlike previously proposed change of measures, the one used here is not static, i.e., it depends on the buffer contents at each of the network nodes. The 'optimal' state-dependent change of measure is determined adaptively during the simulation, using the cross-entropy method. The adaptive state-dependent importance sampling algorithm proposed in this paper yields asymptotically efficient simulation of models for which it is shown (formally or otherwise) that no effective static change of measure exists. Simulation results for queueing models of communication systems are presented to demonstrate the effectiveness of the method.
Year
DOI
Venue
2002
10.1002/ett.4460130403
European Transactions on Telecommunications
Keywords
Field
DocType
buffer overflow,communication system,cross entropy method,importance sampling
Importance sampling,Telecommunications network,Markov process,Computer science,Markov model,Algorithm,Node (networking),Layered queueing network,Queueing theory,Buffer overflow
Journal
Volume
Issue
Citations 
13
4
17
PageRank 
References 
Authors
1.49
7
2
Name
Order
Citations
PageRank
Pieter-Tjerk de Boer118422.82
Victor F. Nicola246884.45