The Transform Likelihood Ratio Method for Rare Event Simulation with Heavy Tails
Queueing Systems: Theory and Applications
Analysis of state-independent importance-sampling measures for the two-node tandem queue
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Asymptotically optimal importance sampling for Jackson networks with a tree topology
Queueing Systems: Theory and Applications
Cross-entropy optimization for sensor selection problems
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
A joint symbol detection algorithm efficient at low SNR for a multi-device STBC-MIMO system
RWS'10 Proceedings of the 2010 IEEE conference on Radio and wireless symposium
Improved cross-entropy method for estimation
Statistics and Computing
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In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for theM/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.