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13013 Efficient heuristics for simulating rare events in queuing networks
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Zaburnenko, T.S. (2008) Efficient heuristics for simulating rare events in queuing networks. PhD thesis, University of Twente. CTIT Ph.D.-thesis series No. 08-111 ISBN 978-90-365-2622-7

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In this thesis we propose state-dependent importance sampling heuristics to estimate the probability of population overflow in queuing networks. These heuristics capture state-dependence along the boundaries (when one or more queues are almost empty) which is crucial for the asymptotic efficiency of the change of measure. The approach does not require difficult (and often intractable) mathematical analysis or costly optimization involved in adaptive importance sampling methodologies. Experimental results on tandem, parallel, feed-forward, and a 2-node feedback Jackson queuing networks as well as a 2-node tandem non-Markovian network suggest that the proposed heuristics yield asymptotically efficient estimators, sometimes with bounded relative error. For these queuing networks no state-independent importance sampling techniques are known to be efficient.

Item Type:PhD Thesis
Supervisors:Haverkort, B.R.H.M.
Assistant Supervisors:de Boer, P.T.
Research Group:EWI-DACS: Design and Analysis of Communication Systems
Research Program:CTIT-DSN: Dependable Systems and Networks
Research Project:EQUIP: Enabling Quality of Service in IP-Based Communication Networks
ID Code:13013
Deposited On:29 September 2008
More Information:statisticsmetis

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