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Heavy-Traffic Analysis of a Multiple-Phase Network with Discriminatory Processor Sharing

Author

Listed:
  • I. M. Verloop

    (BCAM---Basque Center for Applied Mathematics, 48170 Derio, Spain; CWI, 1090 GB Amsterdam, The Netherlands)

  • U. Ayesta

    (BCAM---Basque Center for Applied Mathematics, 48170 Derio, Spain; IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain)

  • R. Núñez-Queija

    (CWI, 1090 GB Amsterdam, The Netherlands; University of Amsterdam, 1018 WB Amsterdam, The Netherlands)

Abstract

We analyze a generalization of the discriminatory processor-sharing (DPS) queue in a heavy-traffic setting. Customers present in the system are served simultaneously at rates controlled by a vector of weights. We assume that customers have phase-type distributed service requirements and allow that customers have different weights in various phases of their service.In our main result we establish a state-space collapse for the queue-length vector in heavy traffic. The result shows that in the limit, the queue-length vector is the product of an exponentially distributed random variable and a deterministic vector. This generalizes a previous result by Rege and Sengupta [Rege, K. M., B. Sengupta. 1996. Queue length distribution for the discriminatory processor-sharing queue. Oper. Res. 44 (4) 653--657], who considered a DPS queue with exponentially distributed service requirements. Their analysis was based on obtaining all moments of the queue-length distributions by solving systems of linear equations. We undertake a more direct approach by showing that the probability-generating function satisfies a partial differential equation that allows a closed-form solution after passing to the heavy-traffic limit.Making use of the state-space collapse result, we derive interesting properties in heavy traffic: (i) For the DPS queue, we obtain that, conditioned on the number of customers in the system, the residual service requirements are asymptotically independent and distributed according to the forward recurrence times. (ii) We then investigate how the choice for the weights influences the asymptotic performance of the system. In particular, for the DPS queue we show that the scaled holding cost reduces as classes with a higher value for d k / E ( B k fwd ) obtain a larger share of the capacity, where d k is the cost associated to class k , and E ( B k fwd ) is the forward recurrence time of the class- k service requirement. The applicability of this result for a moderately loaded system is investigated by numerical experiments.

Suggested Citation

  • I. M. Verloop & U. Ayesta & R. Núñez-Queija, 2011. "Heavy-Traffic Analysis of a Multiple-Phase Network with Discriminatory Processor Sharing," Operations Research, INFORMS, vol. 59(3), pages 648-660, June.
  • Handle: RePEc:inm:oropre:v:59:y:2011:i:3:p:648-660
    DOI: 10.1287/opre.1110.0914
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    References listed on IDEAS

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    1. Kiran M. Rege & Bhaskar Sengupta, 1996. "Queue-Length Distribution for the Discriminatory Processor-Sharing Queue," Operations Research, INFORMS, vol. 44(4), pages 653-657, August.
    2. Haviv, Moshe & van der Wal, Jan, 2008. "Mean sojourn times for phase-type discriminatory processor sharing systems," European Journal of Operational Research, Elsevier, vol. 189(2), pages 375-386, September.
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    Cited by:

    1. Rob Mei & Sandjai Bhulai, 2022. "A data-driven approach to deriving closed-form approximations for queueing problems using genetic algorithms," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 549-551, April.
    2. H. Thorsdottir & I. M. Verloop, 2016. "Markov-modulated M/G/1-type queue in heavy traffic and its application to time-sharing disciplines," Queueing Systems: Theory and Applications, Springer, vol. 83(1), pages 29-55, June.

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