Bayesian prediction of the transient behaviour and busy period in short- and long-tailed GI/G/1 queueing systems

Authors:
M. Concepción Ausín;Michael P. Wiper;Rosa E. Lillo
Affiliations:
Department of Mathematics, Facultad de Informática, Campus de Elviña, Universidade da Coruña,15071 A Coruña, Spain;Department of Statistics, Universidad Carlos III de Madrid, 28903 Getafe, Madrid, Spain;Department of Statistics, Universidad Carlos III de Madrid, 28903 Getafe, Madrid, Spain
Venue:
Computational Statistics & Data Analysis
Year:
2008

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Abstract

Bayesian inference for the transient behaviour and duration of a busy period in a single server queueing system with general, unknown distributions for the interarrival and service times is investigated. Both the interarrival and service time distributions are approximated using the dense family of Coxian distributions. A suitable reparameterization allows the definition of a non-informative prior, and Bayesian inference is then undertaken using reversible jump Markov chain Monte Carlo methods. An advantage of the proposed procedure is that heavy-tailed interarrival and service time distributions such as the Pareto can be well approximated. The proposed procedure for estimating the system measures is based on recent theoretical results for the Coxian/Coxian/1 system. A numerical technique is developed for every MCMC iteration so that the transient queue length and waiting time distributions and the duration of a busy period can be estimated. The approach is illustrated with both simulated and real data.