Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-10T21:14:43.676Z Has data issue: false hasContentIssue false

Multiserver queueing systems with retrials and losses

Published online by Cambridge University Press:  17 February 2009

Vyacheslav M. Abramov
Affiliation:
School of Mathematical Sciences, Monash University, Building 28M, Clayton Campus, Clayton, VIC 3800, Australia; e-mail: vyacheslav.abramov@sci.monash.edu.au.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The interest in retrial queueing systems mainly lies in their application to telephone systems. This paper studies multiserver retrial queueing systems with n servers. The arrival process is a quite general point process. An arriving customer occupies one of the free servers. If upon arrival all servers are busy, then the customer waits for his service in orbit, and after a random time retries in order to occupy a server. The orbit has one waiting space only, and an arriving customer, who finds all servers busy and the waiting space occupied, is lost from the system. Time intervals between possible retrials are assumed to have arbitrary distribution (the retrial scheme is explained more precisely in the paper). The paper provides analysis of this system. Specifically the paper studies the optimal number of servers to decrease the loss proportion to a given value. The representation obtained for the loss proportion enables us to solve the problem numerically. The algorithm for numerical solution includes effective simulation, which meets the challenge of a rare events problem in simulation.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2007

References

[1]Abramov, V. M., “Analysis of multiserver retrial queueing system: A martingale approach and an algorithm of solution”, Ann. Oper. Res. 141 (2006) 1950.CrossRefGoogle Scholar
[2]Artalejo, J. R., “Accessible bibliography on retrial queues”, Math. Comput. Model. 30 (1999) 16.CrossRefGoogle Scholar
[3]Artalejo, J. R. and Falin, G. I., “Standard and retrial queueing systems. A comparative analysis”, Mat. Complut. 15 (2002) 101129.Google Scholar
[4]Atencia, I. and Phong, N. H., “A queueing system under LCFS PR discipline with Markovian arrival process and general times of searching for service”, Investig. Oper. 25 (2004) 293298.Google Scholar
[5]Bharucha-Reid, A. T., Elements of the theory of Markov processes and their application (McGraw-Hill, New York, 1960).Google Scholar
[6]Bocharov, P. P., D'Apice, C., Manzo, R. and Phong, N. H., “On retrial single-server queueing system with finite buffer and multivariate Poisson flow”, Prob. Inf. Transm. 37 (2001) 397406.CrossRefGoogle Scholar
[7]Bocharov, P. P., Phong, N. H. and Atencia, I., “Retrial queueing systems with several input flows”, Investig. Oper. 22 (2001) 135143.Google Scholar
[8]Cohen, J. W., “The full availability group of trunks with an arbitrary distribution of interarrival times and negative exponential holding time distribution”, Bull. Belg. Math. Soc. Simon Stevin 31 (1957) 169181.Google Scholar
[9]Dellacherie, C., Capacites et Processus Stochastiques (Springer, Berlin, 1972).CrossRefGoogle Scholar
[10]Falin, G. I., “A survey on retrial queues”, Queueing Syst. 7 (1990) 127168.CrossRefGoogle Scholar
[11]Heidelberger, P., “Fast simulation of rare events in queueing and reliability models”, ACM Trans. Model. Comput. Sim. 5 (1995) 4385.CrossRefGoogle Scholar
[12]Jacod, J. and Shiryayev, A. N., Limit theorems for stochastic processes (Springer, Berlin, 1987).CrossRefGoogle Scholar
[13]Kovalenko, I. N., “The loss probability in M/G/m queueing systems with T-retrials in light traffic”, Dopovidi NAN Ukrainy (Ukrainian Academy of Sciences), Ser. A 5 (2002) 7780.Google Scholar
[14]Liptser, R. S. and Shiryayev, A. N., Statistics of random processes. Vols 1, 2. (Springer, Berlin, 1977/1978).CrossRefGoogle Scholar
[15]Liptser, R. S. and Shiryayev, A. N., Theory of martingales (Kluwer, Dordrecht, 1989).CrossRefGoogle Scholar
[16]Mandelbaum, A., Massey, W. A. and Reiman, M. I., “Strong approximation for Markovian service network”, Queueing Syst. 30 (1998) 149201.CrossRefGoogle Scholar
[17]Mandelbaum, A., Massey, W. A., Reiman, M. I., Stolyar, A. and Rider, B., “Queue-lengths and waiting times for multiserver queues with abandonment and retrials“, Telecommunication Syst. 21 (2002) 149171.CrossRefGoogle Scholar
[18]Melamed, B. and Rubinstein, R. Y., Modern simulation and modelling (John Wiley, Chichester, 1998).Google Scholar
[19]Palm, C., “Intensitätschwankungen im Fernsprechverkehr”, Ericsson Technics 44 (1943) 1189.Google Scholar
[20]Pollaczek, F., “Generalisation de la théorie probabiliste des systèmes telephoniques sans dispositif d'attente”, C.R. Math. Acad. Sci. Paris 236 (1953) 14691470.Google Scholar
[21]Rubalskii, G. B., “The search of an extremum of unimodal function of one variable in an unbounded set”, Comput. Math. Math. Phys. 22 (1982) 815. Transl. frm Russian: Zh. Vychisl. Mat. Mat. Fiz. 22 (1982), 10–16, 251.CrossRefGoogle Scholar
[22]Rubinstein, R. Y. and Shapiro, A., Discrete event systems: Sensitivity analysis and stochastic optimization by the score function method (John Wiley, Chichester, 1993).Google Scholar
[23]Shahabuddin, P., “Rare event simulation in stochastic models”, in Proceedings of the 1995 Winter Simulation Conference (eds. Alexopoulos, C., Kang, K., Lilegdon, W. R. and Goldsman, D.), (IEEE Press, 1995) 178185.Google Scholar
[24]Takács, L., “On a probability problem concerning telephone traffic”, Acta Math. Hungar. 8 (1957) 319324.CrossRefGoogle Scholar