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Bittorrent is an auction: analyzing and improving bittorrent's incentives

Published: 17 August 2008 Publication History

Abstract

Incentives play a crucial role in BitTorrent, motivating users to upload to others to achieve fast download times for all peers. Though long believed to be robust to strategic manipulation, recent work has empirically shown that BitTorrent does not provide its users incentive to follow the protocol. We propose an auction-based model to study and improve upon BitTorrent's incentives. The insight behind our model is that BitTorrent uses, not tit-for-tat as widely believed, but an auction to decide which peers to serve. Our model not only captures known, performance-improving strategies, it shapes our thinking toward new, effective strategies. For example, our analysis demonstrates, counter-intuitively, that BitTorrent peers have incentive to intelligently under-report what pieces of the file they have to their neighbors. We implement and evaluate a modification to BitTorrent in which peers reward one another with proportional shares of bandwidth. Within our game-theoretic model, we prove that a proportional-share client is strategy-proof. With experiments on PlanetLab, a local cluster, and live downloads, we show that a proportional-share unchoker yields faster downloads against BitTorrent and BitTyrant clients, and that under-reporting pieces yields prolonged neighbor interest.

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      Published In

      cover image ACM SIGCOMM Computer Communication Review
      ACM SIGCOMM Computer Communication Review  Volume 38, Issue 4
      October 2008
      436 pages
      ISSN:0146-4833
      DOI:10.1145/1402946
      Issue’s Table of Contents
      • cover image ACM Conferences
        SIGCOMM '08: Proceedings of the ACM SIGCOMM 2008 conference on Data communication
        August 2008
        452 pages
        ISBN:9781605581750
        DOI:10.1145/1402958
      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: 17 August 2008
      Published in SIGCOMM-CCR Volume 38, Issue 4

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      Author Tags

      1. auctions
      2. bittorrent
      3. incentive systems
      4. proportional share
      5. tit-for-tat

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      Cited By

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      • (2023)Griefing Factors and Evolutionary In-Stabilities in Blockchain Mining GamesMathematical Research for Blockchain Economy10.1007/978-3-031-18679-0_5(75-94)Online publication date: 19-Feb-2023
      • (2021)Semi-Structured BitTorrent Protocol with Application to Efficient P2P Video StreamingIEICE Transactions on Information and Systems10.1587/transinf.2021EDP7011E104.D:10(1624-1631)Online publication date: 1-Oct-2021
      • (2021)Fair Peer-to-Peer Content Delivery via BlockchainComputer Security – ESORICS 202110.1007/978-3-030-88418-5_17(348-369)Online publication date: 30-Sep-2021
      • (2021)Market Equilibrium Models in Large-Scale Internet MarketsInnovative Technology at the Interface of Finance and Operations10.1007/978-3-030-81945-3_7(147-189)Online publication date: 3-Aug-2021
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      • (2019)Collaborative Caching in P2P Streaming NetworksJournal of Network and Systems Management10.1007/s10922-018-09485-627:3(815-836)Online publication date: 1-Jul-2019
      • (2019)Learnae: Distributed and Resilient Deep Neural Network Training for Heterogeneous Peer to Peer TopologiesPädiatrie10.1007/978-3-030-20257-6_24(286-298)Online publication date: 15-May-2019
      • (2018)Dynamics of Distributed Updating in Fisher MarketsProceedings of the 2018 ACM Conference on Economics and Computation10.1145/3219166.3219189(351-368)Online publication date: 11-Jun-2018
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