A batch-service queueing model with a discrete batch Markovian arrival process

Authors:
Dieter Claeys;Joris Walraevens;Koenraad Laevens;Bart Steyaert;Herwig Bruneel
Affiliations:
Stochastic Modelling and Analysis of Communication Systems Research, Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium;Stochastic Modelling and Analysis of Communication Systems Research, Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium;Stochastic Modelling and Analysis of Communication Systems Research, Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium;Stochastic Modelling and Analysis of Communication Systems Research, Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium;Stochastic Modelling and Analysis of Communication Systems Research, Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium
Venue:
ASMTA'10 Proceedings of the 17th international conference on Analytical and stochastic modeling techniques and applications
Year:
2010

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Abstract

Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of customers in system (system content) reaches or exceeds a threshold. Correlation is taken into account by assuming a discrete batch Markovian arrival process (D-BMAP), i.e. the distribution of the number of customer arrivals per slot depends on a background state which is determined by a first-order Markov chain. We deduce the probability generating function of the system content at random slot marks and we examine the influence of correlation in the arrival process on the behavior of the system. We show that correlation merely has a small impact on the threshold that minimizes the mean system content. In addition, we demonstrate that correlation might have a significant influence on the system content and therefore has to be included in the model.