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A resource-allocation queueing fairness measure

Published: 01 June 2004 Publication History

Abstract

Fairness is a major issue in the operation of queues, perhaps it is the reason why queues were formed in the first place. Recent studies show that the fairness of a queueing system is important to customers not less than the actual delay they experience. Despite this observation little research has been conducted to study fairness in queues, and no commonly agreed upon measure of queue fairness exists. Two recent research exceptions are Avi-Itzhak and Levy [1], where a fairness measure is proposed, and Wierman and Harchol-Balter [18] (this conference, 2003), where a criterion is proposed for classifying service policies as fair or unfair; the criterion focuses on customer service requirement and deals with fairness with respect to service times.In this work we recognize that the inherent behavior of a queueing system is governed by two major factors: Job seniority (arrival times) and job service requirement (service time). Thus, it is desired that a queueing fairness measure would account for both. To this end we propose a Resource Allocation Queueing Fairness Measure, (RAQFM), that accounts for both relative job seniority and relative service time. The measure allows accounting for individual job discrimination as well as system unfairness. The system measure forms a full scale that can be used to evaluate the level of unfairness under various queueing disciplines. We present several basic properties of the measure. We derive the individual measure as well as the system measure for an M/M/1 queue under five fundamental service policies: Processor Sharing (PS), First Come First Served (FCFS), Non-Preemptive Last Come First Served (NP-LCFS), Preemptive Last Come First Served (P-LCFS), and Random Order of Service (ROS). The results of RAQFM are then compared to those of Wierman and Harchol-Balter [18], and the quite intriguing observed differences are discussed.

References

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B. Avi-Itzhak and H. Levy. On measuring fairness in queues. Advances of Applied Probability, to appear, 2004.
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A. Wierman and M. Harchol-Balter. Classifying scheduling policies with respect to unfairness in an M/GI/1. In Proceedings of ACM Sigmetrics 2003 Conference on Measurement and Modeling of Computer Systems, San Diego, CA, June 2003.

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Published In

cover image ACM Conferences
SIGMETRICS '04/Performance '04: Proceedings of the joint international conference on Measurement and modeling of computer systems
June 2004
450 pages
ISBN:1581138733
DOI:10.1145/1005686
  • cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 32, Issue 1
    June 2004
    432 pages
    ISSN:0163-5999
    DOI:10.1145/1012888
    Issue’s Table of Contents
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 June 2004

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Author Tags

  1. FCFS
  2. M/M/1
  3. PS
  4. fairness
  5. job scheduling
  6. processor sharing
  7. queue disciplines
  8. resource allocation
  9. unfairness

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SIGMETRICS04
SIGMETRICS04: SIGMETRICS 2004 / PERFORMANCE 2004
June 10 - 14, 2004
NY, New York, USA

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Overall Acceptance Rate 459 of 2,691 submissions, 17%

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  • (2017)Semantic Optimization in Tractable Classes of Conjunctive QueriesACM SIGMOD Record10.1145/3137586.313758846:2(5-17)Online publication date: 1-Sep-2017
  • (2017)An Evaluation of Optimizing for FUD in Scheduling for Shared Computing Environments2017 IEEE International Conference on Smart Cloud (SmartCloud)10.1109/SmartCloud.2017.48(258-262)Online publication date: Nov-2017
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  • (2014)Balanced resource allocations across multiple dynamic MapReduce clustersThe 2014 ACM international conference on Measurement and modeling of computer systems10.1145/2591971.2591998(329-341)Online publication date: 16-Jun-2014
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