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Online load balancing under graph constraints

Published:17 June 2013Publication History

ABSTRACT

In several data center settings, each arriving job may only be served by one of a subset of servers. Such a graph constraint can arise due to several reasons. One is locality of the data needed by a job; for example, in content farms (e.g. in Netflix or YouTube) a video request can only be served by a machine that possesses a copy. Motivated by this, we consider a setting where each job, on arrival, reveals a deadline and a subset of servers that can serve it. The job needs to be immediately allocated to one of these servers, and cannot be moved thereafter. Our objective is to maximize the fraction of jobs that are served before their deadlines. For this online load balancing problem, we prove an upper bound of 1-1/e on the competitive ratio of non-preemptive online algorithms for systems with a large number of servers. We propose an algorithm - INSERT RANKING - which achieves this upper bound. The algorithm makes decisions in a correlated random way and it is inspired by the work of Karp, Vazirani and Vazirani on online matching for bipartite graphs. We also show that two more natural algorithm, based on independent randomness, are strictly suboptimal, with a competitive ratio of 1/2.

References

  1. B. Kalyanasundaram and K.R. Pruhs. An optimal deterministic algorithm for online b-matching. Theoretical Computer Science, 233:2000, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. R.M. Karp, U.V. Vazirani, and V.V. Vazirani. An optimal algorithm for on-line bipartite matching. In Proceedings of the twenty-second annual ACM symposium on Theory of Computing, Baltimore, Maryland, May 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Mehta, A. Saberi, U. Vazirani, and V. Vazirani. Adwords and generalized on-line matching. In Proceedings of FOCS, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. S. Moharir and S. Sanghavi. Online load balancing and correlated randomness. In Annual Conference on Communication, Control and Computing (Allerton), 2012.Google ScholarGoogle ScholarCross RefCross Ref
  5. www.netflix.com.Google ScholarGoogle Scholar
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  1. Online load balancing under graph constraints

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      • Published in

        cover image ACM Conferences
        SIGMETRICS '13: Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
        June 2013
        406 pages
        ISBN:9781450319003
        DOI:10.1145/2465529
        • cover image ACM SIGMETRICS Performance Evaluation Review
          ACM SIGMETRICS Performance Evaluation Review  Volume 41, Issue 1
          Performance evaluation review
          June 2013
          385 pages
          ISSN:0163-5999
          DOI:10.1145/2494232
          Issue’s Table of Contents

        Copyright © 2013 Copyright is held by the owner/author(s)

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 17 June 2013

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        Acceptance Rates

        SIGMETRICS '13 Paper Acceptance Rate54of196submissions,28%Overall Acceptance Rate459of2,691submissions,17%

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