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Incentive compatibility and dynamics of congestion control

Published: 14 June 2010 Publication History

Abstract

his paper studies under what conditions congestion control schemes can be both efficient, so that capacity is not wasted, and incentive compatible, so that each participant can maximize its utility by following the prescribed protocol. We show that both conditions can be achieved if routers run strict priority queueing (SPQ) or weighted fair queueing (WFQ) and end-hosts run any of a family of protocols which we call Probing Increase Educated Decrease (PIED). A natural question is whether incentive compatibility and efficiency are possible while avoiding the per-flow processing of WFQ. We partially address that question in the negative by showing that any policy satisfying a certain "locality" condition cannot guarantee both properties.
Our results also have implication for convergence to some steady-state throughput for the flows. Even when senders transmit at a fixed rate (as in a UDP flow which does not react to congestion), feedback effects among the routers can result in complex dynamics which do not appear in the simple topologies studied in past work.

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    Published In

    cover image ACM SIGMETRICS Performance Evaluation Review
    ACM SIGMETRICS Performance Evaluation Review  Volume 38, Issue 1
    Performance evaluation review
    June 2010
    382 pages
    ISSN:0163-5999
    DOI:10.1145/1811099
    Issue’s Table of Contents
    • cover image ACM Conferences
      SIGMETRICS '10: Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
      June 2010
      398 pages
      ISBN:9781450300384
      DOI:10.1145/1811039
    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: 14 June 2010
    Published in SIGMETRICS Volume 38, Issue 1

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    Author Tags

    1. TCP
    2. congestion control
    3. incentives
    4. queueing

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    Cited By

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    • (2019)Axiomatizing Congestion ControlProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3341617.33261483:2(1-33)Online publication date: 19-Jun-2019
    • (2018)Rethinking Networking for "Five Computers"Proceedings of the 17th ACM Workshop on Hot Topics in Networks10.1145/3286062.3286076(92-98)Online publication date: 15-Nov-2018
    • (2016)Dynamic Pricing and Traffic Engineering for Timely Inter-Datacenter TransfersProceedings of the 2016 ACM SIGCOMM Conference10.1145/2934872.2934893(73-86)Online publication date: 22-Aug-2016
    • (2015)Can Bandwidth Sharing Be Truthful?Algorithmic Game Theory10.1007/978-3-662-48433-3_15(190-202)Online publication date: 10-Dec-2015
    • (2014)An online auction framework for dynamic resource provisioning in cloud computingACM SIGMETRICS Performance Evaluation Review10.1145/2637364.259198042:1(71-83)Online publication date: 16-Jun-2014
    • (2014)An online auction framework for dynamic resource provisioning in cloud computingThe 2014 ACM international conference on Measurement and modeling of computer systems10.1145/2591971.2591980(71-83)Online publication date: 16-Jun-2014
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    • (2013)A game-theoretic approach to stable routing in max-min fair networksIEEE/ACM Transactions on Networking10.1109/TNET.2013.224741621:6(1947-1959)Online publication date: 1-Dec-2013
    • (2013)CRSG: A congestion control routing algorithm for security defense based on social psychology and game theory in DTNJournal of Central South University10.1007/s11771-013-1505-z20:2(440-450)Online publication date: 7-Feb-2013
    • (2013)Imperfect Best-Response MechanismsAlgorithmic Game Theory10.1007/978-3-642-41392-6_21(243-254)Online publication date: 2013
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