Paper Info
Title
Efficient estimation of overflow probabilities in queues with breakdowns
Abstract
Efficient importance sampling methods are proposed for the simulation of a single server queue with server breakdowns. The server is assumed to alternate between the operational and failure states according to a continuous time Markov chain. Both, continuous (fluid flow) and discrete (single arrivals) sources are considered. In the fluid flow model, we consider Markov-modulated fluid sources and a constant output rate when the server is operational. In the discrete arrivals model, we consider Markov-modulated Poisson sources and generally distributed service time when the server is operational. We show how known results on Markov additive processes may be applied to determine the optimal (exponentially tilted) change of measure for both models. The concept of effective bandwidth is used in models with multiple independent sources. Empirical studies demonstrate the effectiveness of the proposed change of measures when used in importance sampling simulations. (C) 1999 Elsevier Science B.V. All rights reserved.
Year
DOI
Venue
1999
10.1016/S0166-5316(99)00036-X
PERFORMANCE EVALUATION
Keywords
Field
DocType
queues with breakdowns,rare event simulation,importance sampling,Markov-modulated rate processes,effective bandwidth
Importance sampling,Mathematical optimization,Markov process,Continuous-time Markov chain,Simulation,Computer science,Queue,Markov chain,Fluid queue,Bandwidth (signal processing),Sampling (statistics),Distributed computing
Journal
Volume
ISSN
Citations 
36-7
0166-5316
6
PageRank 
References 
Authors
0.48
5
2
Name
Order
Citations
PageRank
Dirk P. Kroese142937.56
Victor F. Nicola246884.45