Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-10T12:30:22.120Z Has data issue: false hasContentIssue false

Polling systems with periodic server routeing in heavy traffic: distribution of the delay

Published online by Cambridge University Press:  14 July 2016

Tava Lennon Olsen*
Affiliation:
Washington University in St. Louis
R. D. van der Mei*
Affiliation:
Vrije Universiteit, Amsterdam, and TNO Telecom
*
Postal address: John M. Olin School of Business, Washington University in St. Louis, Campus Box 1133, St. Louis, MO 63130—4899, USA. Email address: olsen@olin.wustl.edu
∗∗ Postal address: Vrije Universiteit, Faculty of Exact Sciences, 1081HV Amsterdam, Netherlands.

Abstract

We consider polling systems with mixtures of exhaustive and gated service in which the server visits the queues periodically according to a general polling table. We derive exact expressions for the steady-state delay incurred at each of the queues under standard heavy-traffic scalings. The expressions require the solution of a set of only M—N linear equations, where M is the length of the polling table and N is the number of queues, but are otherwise explicit. The equations can even be expressed in closed form for several routeing schemes commonly used in practice, such as the star and elevator visit order, in a general parameter setting. The results reveal a number of asymptotic properties of the behavior of polling systems. In addition, the results lead to simple and fast approximations for the distributions and the moments of the delay in stable polling systems with periodic server routeing. Numerical results demonstrate that the approximations are highly accurate for medium and heavily loaded systems.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2003 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Athreya, K. B., and Ney, P. E. (1971). Branching Processes. Springer, Berlin.Google Scholar
Baccelli, F. and Brémaud, P. (1991). Elements of Queueing Theory. Springer, Berlin.Google Scholar
Baker, J. E., and Rubin, I. R. (1987). Polling with a general-service order table. IEEE Trans. Commun. 35, 283288.Google Scholar
Blanc, J. P. C. (1993). Performance analysis and optimization with the power-series algorithm. In Performance Evaluation of Computer and Communication Systems, eds Donatiello, L. and Nelson, R., Springer, Berlin, pp. 5380.Google Scholar
Boxma, O. J., Groenendijk, W. P., and Weststrate, J. A. (1990). A pseudoconservation law for service systems with a polling table. IEEE Trans. Commun. 38, 18651870.Google Scholar
Choudhury, G., and Whitt, W. (1994). Computing transient and steady state distributions in polling models by numerical transform inversion. Perf. Eval. 25, 267292.CrossRefGoogle Scholar
Choudhury, G. L. (1990). Polling with a general service order table: gated service. In Proc. IEEE INFOCOM '90 (San Francisco, CA), Vol. 1, pp. 268276.Google Scholar
Chung, K. L. (1974). A Course in Probability, 2nd edn. Academic Press, New York.Google Scholar
Coffman, E. G., Puhalskii, A. A., and Reiman, M. I. (1995). Polling systems with zero switch-over times: a heavy-traffic principle. Ann. Appl. Prob. 5, 681719.CrossRefGoogle Scholar
Coffman, E. G., Puhalskii, A. A., and Reiman, M. I. (1998). Polling systems in heavy-traffic: a Bessel process limit. Math. Operat. Res. 23, 257304.Google Scholar
Cohen, J. W., and Boxma, O. J. (1981). The M/G/1 queue with alternating service formulated as a Riemann-Hilbert boundary value problem. In Performance '81 (Proc. 8th Internat. Symp. Comput. Perf. Model., Amsterdam), ed. Kylstra, F. J., North-Holland, Amsterdam, pp. 181199.Google Scholar
Eisenberg, M. (1972). Queues with periodic service and changeover times. Operat. Res. 20, 440451.Google Scholar
Eisenberg, M. (1994). The polling system with a stopping server. Queueing Systems 18, 387431.Google Scholar
Federgruen, A., and Katalan, Z. (1994). Approximating queue size and waiting-time distributions in general polling systems. Queueing Systems 18, 353386.Google Scholar
Federgruen, A., and Katalan, Z. (1998). Determining production schedules under base-stock policies in single facility multi-item production systems. Operat. Res. 46, 883898.Google Scholar
Fricker, C. and Jaïbi, M. R. (1994). Monotonicity and stability of periodic polling models. Queueing Systems 15, 211238.Google Scholar
Fuhrmann, S. W., and Cooper, R. D. (1985). Stochastic decompositions in the M/G/1 queue with generalized vacations. Operat. Res. 33, 11171129.Google Scholar
Harrison, J. M., and Nguyen, V. (1993). Brownian models of multiclass queueing networks: current status and open problems. Queueing Systems 13, 540.CrossRefGoogle Scholar
Jennings, O. B. (1999). Generalized Round Robin Service Disciplines in Stochastic Networks with Setups: Stability Analysis and Diffusion Approximation. , Georgia Institute of Technology, Atlanta.Google Scholar
Konheim, A. G., Levy, H., and Srinivasan, M. M. (1994). Descendant set: an efficient approach for the analysis of polling systems. IEEE Trans. Commun. 42, 12451253.Google Scholar
Kroese, D. P. (1997). Heavy traffic analysis for continuous polling models. J. Appl. Prob. 34, 720732.Google Scholar
Leung, K. K. (1991). Cyclic service systems with probabilistically-limited service. IEEE J. Sel. Areas Commun. 9, 185193.Google Scholar
Levy, H., and Sidi, M. (1991). Polling models: applications, modeling and optimization. IEEE Trans. Commun. 38, 17501760.Google Scholar
Markowitz, D. M., and Wein, L. M. (2001). Heavy traffic analysis of dynamic cyclic policies: a unified treatment of the single machine scheduling problem. Operat. Res. 49, 246270.Google Scholar
Markowitz, D. M., Reiman, M. I., and Wein, L. M. (2000). The stochastic economic lot scheduling problem: heavy traffic analysis of dynamic cyclic policies. Operat. Res. 48, 136154.Google Scholar
Olsen, T. L. (1999). A practical scheduling method for multi-class production systems with setups. Manag. Sci. 45, 116130.Google Scholar
Olsen, T. L. (2001). Approximations for the waiting time distribution in polling models with and without state-dependent setups. Operat. Res. Lett. 28, 113123.Google Scholar
Olsen, T. L. (2001). Limit theorems for polling models with increasing setups. Prob. Eng. Inf. Sci. 15, 3555.Google Scholar
Olsen, T. L. (2001). On multi-item production systems with setups: review and intuition. Working Paper, Washington University in St. Louis.Google Scholar
Reiman, M. I., and Wein, L. M. (1998). Dynamic scheduling of a two-class queue with setups. Operat. Res. 46, 532547.Google Scholar
Reiman, M. I., and Wein, L. M. (1999). Heavy traffic analysis of polling systems in tandem. Operat. Res. 47, 524534.Google Scholar
Reiman, M. I., Rubio, R., and Wein, L. M. (1999). Heavy traffic analysis of the dynamic stochastic inventory-routeing problem. Transport Sci. 33, 361380.CrossRefGoogle Scholar
Resing, J. A. C. (1993). Polling systems and multitype branching processes. Queueing Systems 13, 409426.Google Scholar
Takagi, H. (1986). Analysis of Polling Systems. MIT Press, Cambridge, MA.Google Scholar
Takagi, H. (1990). Queueing analysis of polling models: an update. In Stochastic Analysis of Computer and Communication Systems, ed. Takagi, H., North-Holland, Amsterdam, pp. 267318.Google Scholar
Takagi, H. (1991). Applications of polling models to computer networks. Comput. Networks ISDN Systems 22, 193211.Google Scholar
Takagi, H. (1997). Queueing analysis of polling models: progress in 1990–1994. In Frontiers in Queueing, ed. Dshalalow, J. H., CRC, Boca Raton, FL, pp. 119146.Google Scholar
Takagi, H., and Murata, M. (1986). Queueing analysis of scan-type TDM and polling systems. In Computer Networking and Performance Evaluation, eds Hasegawa, T., Takagi, H. and Takahashi, Y., North-Holland, Amsterdam, pp. 199211.Google Scholar
Van der Mei, R. D. (1999). Delay in polling systems with large switch-over times. J. Appl. Prob. 36, 232243.Google Scholar
Van der Mei, R. D. (1999). Distribution of the delay in polling systems in heavy traffic. Perf. Eval. 38, 133148.Google Scholar
Van der Mei, R. D. (1999). Polling systems in heavy traffic: higher moments of the delay. Queueing Systems 31, 265294.CrossRefGoogle Scholar
Van der Mei, R. D. (1999). Polling systems with periodic server routeing in heavy traffic. Stoch. Models 15, 273297.CrossRefGoogle Scholar
Van der Mei, R. D. (2000). Polling systems with switch-over times under heavy load: moments of the delay. Queueing Systems 36, 381404.Google Scholar
Van der Mei, R. D. (2002). Waiting-time distributions in polling systems with simultaneous batch arrivals. Ann. Operat. Res. 113, 155173.Google Scholar
Van der Mei, R. D., and Borst, S. C. (1997). Analysis of multiple-server polling systems by means of the power-series algorithm. Stoch. Models 13, 339369.CrossRefGoogle Scholar
Van der Mei, R. D., and Levy, H. (1997). Polling systems in heavy traffic: exhaustiveness of service policies. Queueing Systems 27, 227250.Google Scholar
Van der Mei, R. D., and Levy, H. (1998). Expected delay analysis of polling systems in heavy traffic. Adv. Appl. Prob. 30, 586602.Google Scholar
Weststrate, J. A. and Van der Mei, R. D. (1994). Waiting times in a two-queue model with exhaustive and Bernoulli service. Z. Operat. Res. Math. Meth. Operat. Res. 40, 289303.CrossRefGoogle Scholar