Extensions: an efficient importance sampling method for rare event simulation in large scale tandem networks

Authors:
Lei Wei;Honghui Qi
Affiliations:
University of Central Florida, Orlando, FL;Weiston Communications, Winter Park, FL
Venue:
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Year:
2002

Citing 6
Cited 1

Statistical optimization of dynamic importance sampling parameters for efficient simulation of communication networks

IEEE/ACM Transactions on Networking (TON)
Analysis of an importance sampling estimator for tandem queues

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Fast simulation of rare events in queueing and reliability models

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Construction of fast recovery codes using a new optimal importance sampling method

IEEE Transactions on Information Theory
Quick simulation: a review of importance sampling techniques in communications systems

IEEE Journal on Selected Areas in Communications
Estimated bit-error probability of DS-SSMA/MPSK with coherent detector on satellite mobile channel

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Asymptotically optimal importance sampling for Jackson networks with a tree topology

Queueing Systems: Theory and Applications

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Abstract

In this paper, we present a variance minimization (VM) procedure for rare event simulation in tandem queueing networks. We prove that the VM method can produce a zero variance. The VM method is suitable to compute optimal importance sampling (IS) parameters for small scale tandem networks. For large scale tandem networks we propose a sub-optimal IS (SOIS) method, which projects the optimal biased transition probabilities of the corresponding small scale system into those of a large scale system. In other words, we establish an efficient IS method for a large scale system by zooming into a small scale system and then projecting our findings into the large scale system. The numerical results show that our SOIS method can produce accurate results with very short CPU time, while many other methods often require much longer.