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)
Efficient simulation of a tandem Jackson network
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Importance Sampling Simulation of Population Overflow in Two-node Tandem Networks
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Analysis of state-independent importance-sampling measures for the two-node tandem queue
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Previous work on state-dependent adaptive importance sampling techniques for the simulation of rare events in Markovian queueing models used either no smoothing or a parametric smoothing technique, which was known to be non-optimal. In this paper, we introduce the use of kernel smoothing in this conteXt. We derive eXpressions for the smoothed transition probabilities, compare several variations of the technique, and eXplore the choice of kernel width. We provide some eXamples, demonstrating that the technique significantly improves convergence and estimator variance.