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Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 327-343
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
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doi:10.1016/j.peva.2004.10.016    
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Copyright © 2004 Elsevier B.V. All rights reserved.

Optimal control of parallel queues with impatient customers

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Ali MovagharE-mail The Corresponding Author

Department of Computer Engineering, Sharif University of Technology, Tehran, Iran


Available online 20 January 2005.

Abstract

We consider a queueing system with a number of identical exponential servers. Each server has its own queue with unlimited capacity. The service discipline in each queue is first-come-first-served (FCFS). Customers arrive according to a state-dependent Poisson process with an arrival rate which is a non-increasing function of the number of customers in the system. Upon arrival, a customer must join a server’s queue according to a stationary state-dependent policy, where the state is taken to be the number of customers in servers’ queues. No jockeying among queues is allowed. Each arriving customer is limited to a generally distributed patience time after which it must depart the system and is considered lost. Two models of customer behavior are considered: deadlines until the beginning of service and deadlines until the end of service. We seek an optimal policy to assign an arriving customer to a server’s queue. We show that, when the distribution of customer impatience satisfies certain property, the policy of joining shortest queue (SQ) stochastically minimizes the number of lost customers during any finite interval in the long run. This property is shown to always hold for the case of deterministic customer impatience.

Keywords: Control of queues; Markov decision processes; Queues with impatient customers; Real-time scheduling

Article Outline

1. Introduction
2. Loss rates
3. Optimization framework
4. Optimal policy
Acknowledgements
References
Vitae

Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 327-343
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
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