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Beyond Dominant Resource Fairness: Extensions, Limitations, and Indivisibilities

Published: 27 March 2015 Publication History

Abstract

We study the problem of allocating multiple resources to agents with heterogeneous demands. Technological advances such as cloud computing and data centers provide a new impetus for investigating this problem under the assumption that agents demand the resources in fixed proportions, known in economics as Leontief preferences. In a recent paper, Ghodsi et al. [2011] introduced the dominant resource fairness (DRF) mechanism, which was shown to possess highly desirable theoretical properties under Leontief preferences. We extend their results in three directions. First, we show that DRF generalizes to more expressive settings, and leverage a new technical framework to formally extend its guarantees. Second, we study the relation between social welfare and properties such as truthfulness; DRF performs poorly in terms of social welfare, but we show that this is an unavoidable shortcoming that is shared by every mechanism that satisfies one of three basic properties. Third, and most importantly, we study a realistic setting that involves indivisibilities. We chart the boundaries of the possible in this setting, contributing a new relaxed notion of fairness and providing both possibility and impossibility results.

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  • (2024)Multi-resource maximin share fair allocation in the cloud-edge collaborative computing system with bandwidth demand compressionCluster Computing10.1007/s10586-024-04815-728:2Online publication date: 26-Nov-2024
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Information

Published In

cover image ACM Transactions on Economics and Computation
ACM Transactions on Economics and Computation  Volume 3, Issue 1
Special Issue on EC'12, Part 1
March 2015
143 pages
ISSN:2167-8375
EISSN:2167-8383
DOI:10.1145/2752509
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 March 2015
Accepted: 01 April 2014
Revised: 01 November 2013
Received: 01 March 2013
Published in TEAC Volume 3, Issue 1

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Author Tags

  1. Fair division
  2. resource allocation

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  • Refereed

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  • CMU-MSR Center for Computational Thinking
  • NSF

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Cited By

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  • (2024)Distribution of Chores with Information AsymmetryProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3663142(2306-2308)Online publication date: 6-May-2024
  • (2024)Dynamic Multi-Resource Fair Allocation with Elastic DemandsJournal of Grid Computing10.1007/s10723-024-09754-622:1Online publication date: 27-Feb-2024
  • (2024)Multi-resource maximin share fair allocation in the cloud-edge collaborative computing system with bandwidth demand compressionCluster Computing10.1007/s10586-024-04815-728:2Online publication date: 26-Nov-2024
  • (2023)Pushing the limits of fairness in algorithmic decision-makingProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/806(7051-7056)Online publication date: 19-Aug-2023
  • (2023)A Task Scheduling Algorithm for Micro-cloud Platform Based on Task Real-timeProceedings of the 2023 2nd International Conference on Networks, Communications and Information Technology10.1145/3605801.3605839(196-200)Online publication date: 16-Jun-2023
  • (2023)Fair Multi-Resource Allocation in Heterogeneous Servers With an External Resource TypeIEEE/ACM Transactions on Networking10.1109/TNET.2022.321342631:3(1244-1262)Online publication date: Jun-2023
  • (2023)Privacy as a Resource in Differentially Private Federated LearningIEEE INFOCOM 2023 - IEEE Conference on Computer Communications10.1109/INFOCOM53939.2023.10228953(1-10)Online publication date: 17-May-2023
  • (2023)Multi-resource fair allocation with bandwidth requirement compression in the cloud–edge systemComputers and Electrical Engineering10.1016/j.compeleceng.2022.108510105(108510)Online publication date: Jan-2023
  • (2023)Multiresource fair allocation with time window constraintsThe Journal of Supercomputing10.1007/s11227-023-05248-679:14(15927-15954)Online publication date: 22-Apr-2023
  • (2022)R2BProceedings of the 59th ACM/IEEE Design Automation Conference10.1145/3489517.3530521(883-888)Online publication date: 10-Jul-2022
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