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Coupon replication systems

Published: 06 June 2005 Publication History
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  • Abstract

    Motivated by the study of peer-to-peer file swarming systems à la BitTorrent, we introduce a probabilistic model of coupon replication systems. These systems consist of users, aiming to complete a collection of distinct coupons. Users are characterised by their current collection of coupons, and leave the system once they complete their coupon collection. The system evolution is then specified by describing how users of distinct types meet, and which coupons get replicated upon such encounters.For open systems, with exogenous user arrivals, we derive necessary and sufficient stability conditions in a layered scenario, where encounters are between users holding the same number of coupons. We also consider a system where encounters are between users chosen uniformly at random from the whole population. We show that performance, captured by sojourn time, is asymptotically optimal in both systems as the number of coupon types becomes large.We also consider closed systems with no exogenous user arrivals. In a special scenario where users have only one missing coupon, we evaluate the size of the population ultimately remaining in the system, as the initial number of users, N, goes to infinity. We show that this decreases geometrically with the number of coupons, K. In particular, when the ratio K/log(N) is above a critical threshold, we prove that this number of left-overs is of order log(log(N)).These results suggest that performance of file swarming systems does not depend critically on either altruistic user behavior, or on load balancing strategies such as rarest first.

    References

    [1]
    Edonkey. http://www.edonkey2000.com/index.html.
    [2]
    Kazaa. http://www.kazaa.com/.
    [3]
    A. Müller and D. Stoyan. Comparison Methods for Stochastic Models and Risks. Wiley Series in Probability and Statistics, 2002.
    [4]
    N. Alon and J. Spencer. The probabilistic method. Wiley Interscience Series in Discrete Mathematics and Optimization, 2 edition, 2000.
    [5]
    B. Cohen. Incentives Build Robustness in BitTorrent, http://bitconjurer.org/BitTorrent/bittorrentecon.pdf, May 2003.
    [6]
    S. Deb and M. Médard. Algebraic Gossip: A Network Coding Approach to Optimal Multiple Rumor Mongering, April 2004. preprint.
    [7]
    D. Qiu and R. Srikant. Modeling and Performance Analysis of BitTorrent-Like Peer-to-Peer Networks. In Proc. of ACM Sigcomm 2004, Portland, Oregon, 2004.
    [8]
    G. Hardy, J. E. Littlewood, and G. Pólya. Inequalities. Cambridge Mathematical Library, 2 edition, 1952.
    [9]
    R. L. Graham, D. E. Knuth, and O. Patashnik. Concrete Mathematics. Addison Wesley, 1998.
    [10]
    J. Hofbauer and K. Sigmund. Evolutionary Games and Population Dynamics. Cambridge University Press, 1998.
    [11]
    J. A. Pouwelse, P. Garbacki, D. H. J. Epema, and H. J. Sips. The BitTorrent P2P File-sharing System: Measurement and Analysis. In Proc. IPTPS'05, Feb 2005.
    [12]
    H. K. Khalil. Nonlinear Systems. Prentice Hall, 3 edition, 2002.
    [13]
    T. Kurtz. Approximation of Population Processes, volume 36. CBMS-NSF Regional Conference Series in Applied Mathematics, 1981.
    [14]
    R. Loynes. The stability of a queue with non-independent inter-arrival and service times. Proc. of Cambr. Phil. Soc., 58(3):497--520, 1962.
    [15]
    M. Izal, G. Urvoy-Keller, E. W. Biersack, P. A. Felber, A. Al Hamra, and L. Garcés-Erice. Dissecting BitTorrent: Five Months in a Torrent's Life. In Proc. of PAM~2004, Antibes, France, 2004.
    [16]
    J. Mundinger and R. Weber. Efficient File Dissemination using Peer-to-Peer Technology. Tech. Rep. 2004-01, University of Cambridge, UK, 2004.
    [17]
    X. Yang and G. de Veciana. Service Capacity of Peer to Peer Networks. In Proc. of Infocom 2004, Hong-Kong, China, 2004.

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    cover image ACM Conferences
    SIGMETRICS '05: Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
    June 2005
    428 pages
    ISBN:1595930221
    DOI:10.1145/1064212
    • cover image ACM SIGMETRICS Performance Evaluation Review
      ACM SIGMETRICS Performance Evaluation Review  Volume 33, Issue 1
      Performance evaluation review
      June 2005
      417 pages
      ISSN:0163-5999
      DOI:10.1145/1071690
      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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    Publication History

    Published: 06 June 2005

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    Author Tags

    1. content distribution
    2. file swarming
    3. peer-to-peer

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

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    • (2023)Data flow dissemination in a networkQueueing Systems10.1007/s11134-023-09896-6105:3-4(317-354)Online publication date: 21-Nov-2023
    • (2022)Refining Mean-field Approximations by Dynamic State TruncationACM SIGMETRICS Performance Evaluation Review10.1145/3543516.346009949:1(31-32)Online publication date: 7-Jun-2022
    • (2021)Refining Mean-field Approximations by Dynamic State TruncationProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/34600925:2(1-30)Online publication date: 4-Jun-2021
    • (2021)Refining Mean-field Approximations by Dynamic State TruncationAbstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems10.1145/3410220.3460099(31-32)Online publication date: 31-May-2021
    • (2016)A performance study of incentive schemes in peer-to-peer file-sharing systemsThe Journal of Supercomputing10.1007/s11227-016-1648-472:3(1152-1178)Online publication date: 1-Mar-2016
    • (2015)Coalitions improve performance in data swarming systemsIEEE/ACM Transactions on Networking10.1109/TNET.2014.234557423:6(1790-1804)Online publication date: 1-Dec-2015
    • (2015)Turbocharged Video Distribution via P2PIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2014.235109325:2(287-299)Online publication date: Feb-2015
    • (2015)Stable and scalable universal swarmsDistributed Computing10.1007/s00446-014-0228-128:6(391-406)Online publication date: 1-Dec-2015
    • (2013)Stable and scalable universal swarmsACM SIGMETRICS Performance Evaluation Review10.1145/2494232.246553741:1(369-370)Online publication date: 17-Jun-2013
    • (2013)Stable and scalable universal swarmsProceedings of the 2013 ACM symposium on Principles of distributed computing10.1145/2484239.2484272(260-269)Online publication date: 22-Jul-2013
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