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Managing Queues with Heterogeneous Servers

Published online by Cambridge University Press:  14 July 2016

Jung Hyun Kim*
Affiliation:
Korea Telecommunication Corporation
Hyun-Soo Ahn*
Affiliation:
University of Michigan
Rhonda Righter*
Affiliation:
University of California, Berkeley
*
Email address: [email protected]
∗∗Postal address: Ross School of Business, University of Michigan, 701 Tappan Street, Ann Arbor, MI 48109-1234, USA. Email address: [email protected]
∗∗∗Postal address: Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720, USA. Email address: [email protected]
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Abstract

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We consider several versions of the job assignment problem for an M/M/m queue with servers of different speeds. When there are two classes of customers, primary and secondary, the number of secondary customers is infinite, and idling is not permitted, we develop an intuitive proof that the optimal policy that minimizes the mean waiting time has a threshold structure. That is, for each server, there is a server-dependent threshold such that a primary customer will be assigned to that server if and only if the queue length of primary customers meets or exceeds the threshold. Our key argument can be generalized to extend the structural result to models with impatient customers, discounted waiting time, batch arrivals and services, geometrically distributed service times, and a random environment. We show how to compute the optimal thresholds, and study the impact of heterogeneity in server speeds on mean waiting times. We also apply the same machinery to the classical slow-server problem without secondary customers, and obtain more general results for the two-server case and strengthen existing results for more than two servers.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2011 

References

[1] Agrawala, A. K., Coffman, E. G. Jr., Garey, M. R. and Tripathi, S. K. (1984). A stochastic optimization algorithm minimizing expected flow times on uniform processors. IEEE Trans. Comput. 33, 351356.Google Scholar
[2] Armony, M. and Mandelbaum, A. (2011). Routing and staffing in large-scale service systems: the case of homogeneous impatient customers and heterogeneous servers. Operat. Res. 59, 5065.Google Scholar
[3] Armony, M. and Ward, A. R. (2010). Fair dynamic routing in large-scale heterogeneous-server systems. Operat. Res. 58, 624637.Google Scholar
[4] De Vericourt, F. and Zhou, Y.-P. (2006). On the incomplete results for the heterogeneous server problem. Queueing Systems 52, 189191.Google Scholar
[5] Koole, G. (1995). A simple proof of the optimality of a threshold policy in a two-server queueing system. Systems Control Lett. 26, 301303.Google Scholar
[6] Kumar, P. R. and Walrand, J. (1985). Individually optimal routing in parallel systems. J. Appl. Prob. 22, 989995.Google Scholar
[7] Lin, W. and Kumar, P. R. (1984). Optimal control of a queueing system with two heterogeneous servers. IEEE Trans. Automatic Control 29, 696703.Google Scholar
[8] Luh, H. P. and Viniotis, I. (2002). Threshold control policies for heterogeneous server systems. Math. Meth. Operat. Res. 55, 121142.Google Scholar
[9] Righter, R. (1988). Job scheduling to minimize expected weighted flowtime on uniform processors. Systems Control Lett. 10, 211216.Google Scholar
[10] Righter, R. and Xu, S. (1991). Scheduling Jobs on heterogeneous processors. Ann. Operat. Res. 29, 587601.Google Scholar
[11] Righter, R. and Xu, S. H. (1991). Scheduling Jobs on nonidentical IFR processors to minimize general cost functions. Adv. Appl. Prob. 23, 909924.Google Scholar
[12] Rosberg, Z. and Makowski, A. M. (1990). Optimal routing to parallel heterogeneous servers—small arrival rates. IEEE Trans. Automatic Control 35, 789796.Google Scholar
[13] Rykov, V. V. (2001). Monotone control of queueing systems with heterogeneous servers. Queueing Systems 37, 391403.Google Scholar
[14] Singh, V. P. and Prasad, J. (1976). A heterogeneous system with finite waiting space. J. Eng. Math. 10, 125134.Google Scholar
[15] Stockbridge, R. H. (1991). A martingale approach to the slow server problem. J. Appl. Prob. 28, 480486.Google Scholar
[16] Weber, R. (1993). On a conjecture about assigning Jobs to processors of differing speeds. IEEE Trans. Automatic Control 38, 166170.Google Scholar
[17] Walrand, J. (1984). A note on: “Optimal control of a queuing system with two heterogeneous servers”. Systems Control Lett. 4, 131134.Google Scholar
[18] Xu, S. H. (1994). A duality approach to admission and scheduling controls of queues. Queueing Systems 18, 273300.Google Scholar
[19] Xu, S. H. and Shanthikumar, J. G. (1993). Optimal expulsion control—a dual approach to admission control of an ordered-entry system. Operat. Res. 41, 11371152.Google Scholar