Abstract
In this paper, we present a basic discrete-time queueing model whereby the service process is decomposed in two (variable) components: the demand of each customer, expressed in a number of work units needed to provide full service of the customer, and the capacity of the server, i.e., the number of work units that the service facility is able to perform per time unit. The model is closely related to multi-server queueing models with server interruptions, in the sense that the service facility is able to deliver more than one unit of work per time unit, and that the number of work units that can be executed per time unit is not constant over time.
Although multi-server queueing models with server interruptions—to some extent—allow us to study the concept of variable capacity, these models have a major disadvantage. The models are notoriously hard to analyze and even when explicit expressions are obtained, these contain various unknown probabilities that have to be calculated numerically, which makes the expressions difficult to interpret. For the model in this paper, on the other hand, we are able to obtain explicit closed-form expressions for the main performance measures of interest. Possible applications of this type of queueing model are numerous: the variable service capacity could model variable available bandwidths in communication networks, a varying production capacity in factories, a variable number of workers in an HR-environment, varying capacity in road traffic, etc.
Similar content being viewed by others
Notes
This paper is an extended version of our conference paper Bruneel et al. (2012).
References
Adan, I. J. B. F., van Leeuwaarden, J. S. H., & Winands, E. M. M. (2006). On the application of Rouché’s theorem in queueing theory. Operations Research Letters, 34, 355–360.
Ayed, S., Dellagi, S., & Rezg, N. (2011). Optimal integrated maintenance production strategy with variable production rate for random demand and subcontracting constraint. In Proceedings of the 18th IFAC World Congress, 2011.
Bruneel, H. (1983a). Buffers with stochastic output interruptions. Electronics Letters, 19, 735–737.
Bruneel, H. (1983b). On the behavior of buffers with random server interruptions. Performance Evaluation, 3(3), 165–175.
Bruneel, H. (1984a). Analysis of an infinite buffer system with random server interruptions. Computers & Operations Research, 11(4), 373–386.
Bruneel, H. (1984b). A general model for the behaviour of infinite buffers with periodic service opportunities. European Journal of Operational Research, 16(1), 98–106.
Bruneel, H. (1984c). A mathematical model for discrete-time buffer systems with correlated output process. European Journal of Operational Research, 18(1), 98–110.
Bruneel, H. (1985). A discrete-time queueing system with a stochastic number of servers subjected to random interruptions. Opsearch, 22(4), 215–231.
Bruneel, H. (1986). A general treatment of discrete-time buffers with one randomly interrupted output line. European Journal of Operational Research, 27(1), 67–81.
Bruneel, H. (1993). Performance of discrete-time queueing systems. Computers & Operations Research, 20(3), 303–320.
Bruneel, H., & Kim, B. G. (1993). Discrete-time models for communication systems including ATM. Boston: Kluwer Academic.
Bruneel, H., Walraevens, J., Claeys, D., & Wittevrongel, S. (2012). Analysis of a discrete-time queue with geometric service capacities. In Proceedings of the 19th international conference on analytical and stochastic modelling techniques and applications (ASMTA’12), Grenoble (pp. 121–135).
Chakravarthy, S. R. (2009). Analysis of a multi-server queue with Markovian arrivals and synchronous phase type vacations. Asia-Pacific Journal of Operational Research, 26(1), 85–113.
Chang, C. S., & Thomas, J. A. (1995). Effective bandwidth in high-speed digital networks. IEEE Journal on Selected Areas in Communications, 13, 1091–1100.
Fiems, D., & Bruneel, H. (2002). A note on the discretization of Little’s result. Operations Research Letters, 30, 17–18.
Fiems, D., Steyaert, B., & Bruneel, H. (2004). Discrete-time queues with generally distributed service times and renewal-type server interruptions. Performance Evaluation, 35, 277–298.
Gao, P., Wittevrongel, S., & Bruneel, H. (2004). Discrete-time multiserver queues with geometric service times. Computers & Operations Research, 31, 81–99.
Gao, P., Wittevrongel, S., Laevens, K., De Vleeschauwer, D., & Bruneel, H. (2010). Distributional Little’s law for queues with heterogeneous server interruptions. Electronics Letters, 46, 763–764.
Georganas, N. D. (1976). Buffer behavior with Poisson arrivals and bulk geometric service. IEEE Transactions on Communications, 24, 938–940.
Giri, B. C., Yun, W. Y., & Dohi, T. (2005). Optimal design of unreliable production–inventory systems with variable production rate. European Journal of Operational Research, 162(2), 372–386.
Glock, C. H. (2010). Batch sizing with controllable production rates. International Journal of Production Research, 48, 5925–5942.
Heines, T. S. (1979). Buffer behavior in computer communication systems. IEEE Transactions on Computers, 28, 573–576.
Hsu, J. (1974). Buffer behavior with Poisson arrival and geometric output process. IEEE Transactions on Communications, 22, 1940–1941.
Hwang, Z., Kim, J., & Rhee, S. (2005). Development of a new highway capacity estimation method. In Proceedings of the Eastern Asia society for transportation studies (pp. 984–995).
Jin, X., Min, G., & Velentzas, S. R. (2008). An analytical queuing model for long range dependent arrivals and variable service capacity. In Proceedings of IEEE international conference on communications (ICC 2008), Beijing, May 2008 (pp. 230–234).
Kafetzakis, E., Kontovasilis, K., & Stavrakakis, I. (2011). Effective-capacity-based stochastic delay guarantees for systems with time-varying servers, with an application to IEEE 802.11 WLANs. Performance Evaluation, 68, 614–628.
Kamoun, F. (2009). Performance evaluation of a queuing system with correlated packet-trains and server interruption. Telecommunications Systems, 41(4), 267–277.
Laevens, K., & Bruneel, H. (1995). Delay analysis for discrete-time queueing systems with multiple randomly interrupted servers. Central European Journal of Operations Research, 85, 161–177.
Lee, D.-S. (1997). Analysis of a single server queue with semi-Markovian service interruption. Queueing Systems, 27, 153–178.
Maertens, T., Walraevens, J., & Bruneel, H. (2007). A modified HOL priority scheduling discipline: performance analysis. Central European Journal of Operations Research, 180, 1168–1185.
Malchin, C., & Daduna, H. (2010). Discrete time queueing networks with product form steady state. Availability and performance analysis in an integrated model. Queueing Systems, 65, 385–421.
Mehmet, A. M., Zhang, X., & Hayes, J. F. (2003). A performance analysis of a discrete-time queueing system with server interruption for modeling wireless atm multiplexer. Performance Evaluation, 51, 1–31.
Mitrani, I. (1987). Modelling of computer and communication systems. Cambridge: Cambridge University Press.
Morris, B., Notley, S., Boddington, K., & Rees, T. (2011). External factors affecting motorway capacity. Procedia Social and Behavioral Sciences, 16, 69–75.
Papoulis, A., & Pillai, S. U. (2002). Probability, random variables, and stochastic processes (4th ed.). New York: McGraw-Hill.
Takagi, H. (1993). Discrete-time systems: Vol. 3. Queueing analysis, a foundation of performance evaluation. Amsterdam: North-Holland.
Takine, T., & Sengupta, B. (1997). A single server queue with service interruptions. Queueing Systems, 26, 285–300.
Yang, X. L., & Alfa, A. S. (2009). A class of multi-server queueing system with server failures. Computers & Industrial Engineering, 56(1), 33–43.
Yu, M. M., Tang, Y. H., Fu, Y. H., & Pan, L. M. (2011). An M/E(k)/1 queueing system with no damage service interruptions. Mathematical and Computer Modelling, 54(5–6), 1262–1272.
Zied, H., Sofiene, D., & Nidhal, R. (2009). An optimal production/maintenance planning under stochastic random demand, service level and failure rate. In Proceedings of the IEEE international conference on automation science and engineering, 2009 (CASE 2009) (pp. 292–297).
Acknowledgement
This research has been funded by the Interuniversity Attraction Poles Programme initiated by the Belgian Science Policy Office.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bruneel, H., Wittevrongel, S., Claeys, D. et al. Discrete-time queues with variable service capacity: a basic model and its analysis. Ann Oper Res 239, 359–380 (2016). https://doi.org/10.1007/s10479-013-1428-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-013-1428-y