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Optimal dynamic scheduling of a general class of parallel-processing queueing systems

Part of: Operations research and management science Computer system organization Special processes Stochastic systems and control

Published online by Cambridge University Press:  01 July 2016

Noah Gans  and
Garrett van Ryzin
Noah Gans*
Affiliation:
University of Pennsylvania
Garrett van Ryzin*
Affiliation:
Columbia University
*
∗ Postal address: OPIM Department, The Wharton School, University of Pennsylvania, Philadelphia PA 19104-6366, USA.
∗∗ Postal address: Graduate School of Business, Columbia University, New York, NY 10027, USA.
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Abstract

In this paper we develop policies for scheduling dynamically arriving jobs to a broad class of parallel-processing queueing systems. We show that in heavy traffic the policies asymptotically minimize a measure of the expected system backlog, which we call system work. Our results yield succinct, closed-form expressions for optimal system work in heavy traffic.

Keywords

Parallel processor queueing systemsdynamic nonpreemptive schedulingoptimal stochastic control

MSC classification

Primary: 60K25: Queueing theory
Secondary: 68M20: Performance evaluation; queueing; scheduling 90B22: Queues and service 90B35: Scheduling theory, deterministic 93E20: Optimal stochastic control
Type
General Applied Probability
Information
Advances in Applied Probability , Volume 30 , Issue 4 , December 1998 , pp. 1130 - 1156
Copyright
Copyright © Applied Probability Trust 1998 

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Footnotes

This is a revision of a working paper dated 17 November 1995.

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