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Randomized routing schemes for large processor sharing systems with multiple service rates

Published: 16 June 2014 Publication History

Abstract

We consider randomized job routing techniques for a system consisting of a large number of parallel processor sharing servers with heterogeneous server speeds. In particular, a scheme, that routes an incoming job request to the server providing the highest instantaneous processing rate per job among two servers, chosen uniformly at random, is proposed. We show that, unlike the homogeneous case, in the heterogeneous case, such randomized dynamic schemes need not always perform better than the optimal static scheme (in which jobs are assigned to servers with fixed probabilities independent of server states) in terms of reducing the mean response time of jobs. Specifically, we show that the stability region under the proposed scheme is a subset of that under the optimal static routing scheme. We also obtain the stationary tail distribution of server occupancies for the proposed scheme in the limit as the system size grows to infinity. This distribution has been shown to be insensitive to job length distribution and decay super-exponentially.

References

[1]
N. D. Vvedenskaya, R. L. Dobrushin, and F. I. Karpelevich. Queueing system with selection of the shortest of two queues: an asymptotic approach. Problems of Information Transmission, 32(1):20--34, 1996.
[2]
M. Bramson, Y. Lu, and B. Prabhakar. Randomized load balancing with general service time distributions. In Proceedings of ACM SIGMETRICS, pages 275--286, 2010.
[3]
E. Altman, U. Ayesta, and B. J. Prabhu. Load balancing in processor sharing systems. Telecommunication Systems, 47(1--2):35--48, 2008.

Cited By

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  • (2021)Optimal hyper-scalable load balancing with a strict queue limitPerformance Evaluation10.1016/j.peva.2021.102217(102217)Online publication date: Jun-2021
  • (2019)Hyper-Scalable JSQ with Sparse FeedbackProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3322205.33110753:1(1-37)Online publication date: 26-Mar-2019
  • (2019)Hyper-Scalable JSQ with Sparse FeedbackProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3322205.33110753:1(1-37)Online publication date: 26-Mar-2019

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    Published In

    cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 42, Issue 1
    Performance evaluation review
    June 2014
    569 pages
    ISSN:0163-5999
    DOI:10.1145/2637364
    Issue’s Table of Contents
    • cover image ACM Conferences
      SIGMETRICS '14: The 2014 ACM international conference on Measurement and modeling of computer systems
      June 2014
      614 pages
      ISBN:9781450327893
      DOI:10.1145/2591971
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 16 June 2014
    Published in SIGMETRICS Volume 42, Issue 1

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    Author Tags

    1. asymptotic independence
    2. insensitivity
    3. load balancing
    4. mean-field analysis
    5. power-of-two

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    Cited By

    View all
    • (2021)Optimal hyper-scalable load balancing with a strict queue limitPerformance Evaluation10.1016/j.peva.2021.102217(102217)Online publication date: Jun-2021
    • (2019)Hyper-Scalable JSQ with Sparse FeedbackProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3322205.33110753:1(1-37)Online publication date: 26-Mar-2019
    • (2019)Hyper-Scalable JSQ with Sparse FeedbackProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3322205.33110753:1(1-37)Online publication date: 26-Mar-2019

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