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Importance Sampling for a Markov Modulated Queuing Network with Customer Impatience until the End of Service

Author

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  • Ebrahim MAHDIPOUR
  • Amir Masoud RAHMANI
  • Saeed SETAYESHI

Abstract

For more than two decades, there has been a growing of interest in fast simulation techniques for estimating probabilities of rare events in queuing networks. Importance sampling is a variance reduction method for simulating rare events. The present paper carries out strict deadlines to the paper by Dupuis et al for a two node tandem network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We derive a closed form solution for the probability of missing deadlines. Then we have employed the results to an importance sampling technique to estimate the probability of total population overflow which is a rare event. We have also shown that the probability of this rare event may be affected by various deadline values.

Suggested Citation

  • Ebrahim MAHDIPOUR & Amir Masoud RAHMANI & Saeed SETAYESHI, 2009. "Importance Sampling for a Markov Modulated Queuing Network with Customer Impatience until the End of Service," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 13(3), pages 106-118.
    • Handle: RePEc:aes:infoec:v:13:y:2009:i:3:p:106-118
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