An M[X]/G/1 retrial queue with server breakdowns and constant rate of repeated attempts

• Published in: Annals of operations research Vol. 157; no. 1; pp. 225 - 243
• Main Authors: Atencia, I., Bouza, G., Moreno, P.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.01.2008; Springer Nature B.V
• Subjects: Business and Management; Combinatorics; Communication; Customer services; Decomposition; Markov analysis; Operations research; Operations Research/Decision Theory; Queuing; Servers; Service stations; Studies; Systems analysis; Theory of Computation; Embedded Markov chain; Busy period; Steady-state distribution; Ergodicity; Reliability analysis; Stochastic decomposition; Number of served customers
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-007-0192-2

We consider an M [ X ] / G /1 retrial queue subject to breakdowns where the retrial time is exponential and independent of the number of customers applying for service. If a coming batch of customers finds the server idle, one of the arriving customers begins his service immediately and the rest joins a retrial group (called orbit) to repeat his request later; otherwise, if the server is busy or down, all customers of the coming batch enter the orbit. It is assumed that the server has a constant failure rate and arbitrary repair time distribution. We study the ergodicity of the embedded Markov chain, its stationary distribution and the joint distribution of the server state and the orbit size in steady-state. The orbit and system size distributions are obtained as well as some performance measures of the system. The stochastic decomposition property and the asymptotic behavior under high rate of retrials are discussed. We also analyse some reliability problems, the k -busy period and the ordinary busy period of our retrial queue. Besides, we give a recursive scheme to compute the distribution of the number of served customers during the k -busy period and the ordinary busy period. The effects of several parameters on the system are analysed numerically.