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A Stochastic Network Under Proportional Fair Resource Control---Diffusion Limit with Multiple Bottlenecks

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  • Heng-Qing Ye

    (Department of Logistics and Maritime Studies, Hong Kong Polytechnic University, Hong Kong)

  • David D. Yao

    (Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

Abstract

We study a multiclass stochastic processing network operating under the so-called proportional fair allocation scheme, and following the head-of-the-line processor-sharing discipline. Specifically, each server's capacity is shared among the job classes that require its service, and it is allocated, in every state of the network, among the first waiting job of each class to maximize a log-utility function. We establish the limiting regime of the network under diffusion scaling, allowing multiple bottlenecks in the network, and relaxing some of the conditions required in prior studies. We also identify the class of allocation schemes among which the proportional fair allocation minimizes a quadratic cost objective function of the diffusion-scaled queue lengths, and we illustrate the limitation of this asymptotic optimality through a counterexample.

Suggested Citation

  • Heng-Qing Ye & David D. Yao, 2012. "A Stochastic Network Under Proportional Fair Resource Control---Diffusion Limit with Multiple Bottlenecks," Operations Research, INFORMS, vol. 60(3), pages 716-738, June.
    • Handle: RePEc:inm:oropre:v:60:y:2012:i:3:p:716-738
    DOI: 10.1287/opre.1120.1047
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    References listed on IDEAS

    as
    1. Heng-Qing Ye & Jihong Ou & Xue-Ming Yuan, 2005. "Stability of Data Networks: Stationary and Bursty Models," Operations Research, INFORMS, vol. 53(1), pages 107-125, February.
    2. Heng-Qing Ye & David D. Yao, 2010. "Utility-Maximizing Resource Control: Diffusion Limit and Asymptotic Optimality for a Two-Bottleneck Model," Operations Research, INFORMS, vol. 58(3), pages 613-623, June.
    3. Avishai Mandelbaum & Alexander L. Stolyar, 2004. "Scheduling Flexible Servers with Convex Delay Costs: Heavy-Traffic Optimality of the Generalized cμ-Rule," Operations Research, INFORMS, vol. 52(6), pages 836-855, December.
    4. Heng-Qing Ye & David D. Yao, 2008. "Heavy-Traffic Optimality of a Stochastic Network Under Utility-Maximizing Resource Allocation," Operations Research, INFORMS, vol. 56(2), pages 453-470, April.
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    Cited by:

    1. Heng-Qing Ye & David D. Yao, 2016. "Diffusion Limit of Fair Resource Control—Stationarity and Interchange of Limits," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1161-1207, November.
    2. Maury Bramson & Bernardo D’Auria & Neil Walton, 2017. "Proportional Switching in First-in, First-out Networks," Operations Research, INFORMS, vol. 65(2), pages 496-513, April.
    3. Anton Braverman, 2020. "Steady-State Analysis of the Join-the-Shortest-Queue Model in the Halfin–Whitt Regime," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 1069-1103, August.
    4. Chihoon Lee & Amy R. Ward & Heng-Qing Ye, 2020. "Stationary distribution convergence of the offered waiting processes for $$GI/GI/1+GI$$GI/GI/1+GI queues in heavy traffic," Queueing Systems: Theory and Applications, Springer, vol. 94(1), pages 147-173, February.

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