Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers

Research Article

Incentivizing Upload Capacity in P2P-VoD Systems: A Game Theoretic Analysis

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  • @INPROCEEDINGS{10.1007/978-3-642-30373-9_24,
        author={Weijie Wu and John Lui and Richard Ma},
        title={Incentivizing Upload Capacity in P2P-VoD Systems: A Game Theoretic Analysis},
        proceedings={Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers},
        proceedings_a={GAMENETS},
        year={2012},
        month={10},
        keywords={P2P-VoD incentive mean field Stackelberg game},
        doi={10.1007/978-3-642-30373-9_24}
    }
    
  • Weijie Wu
    John Lui
    Richard Ma
    Year: 2012
    Incentivizing Upload Capacity in P2P-VoD Systems: A Game Theoretic Analysis
    GAMENETS
    Springer
    DOI: 10.1007/978-3-642-30373-9_24
Weijie Wu1,*, John Lui1,*, Richard Ma2,*
  • 1: The Chinese University of Hong Kong
  • 2: UIUC and National University of Singapore
*Contact email: wjwu@cse.cuhk.edu.hk, cslui@cse.cuhk.edu.hk, tbma@comp.nus.edu.sg

Abstract

Free riding has long been a serious problem in peer-to-peer (P2P) systems due to the selfish behavior of individual users. To conquer this problem, a key design issue of the P2P systems is to appropriately incentivize users to contribute resources. In P2P Video-on-Demand (VoD) applications, content providers need to incentivize the peers to dedicate bandwidth and upload data to one another so as to alleviate the upload workload of their content servers. In this paper, we design a simple yet practical incentive mechanism that rewards each peer based on its dedicated upload bandwidth. We use a interaction model to characterize the distribution of number of peers in different video segments, based on which we characterize the content providers’ uploading cost as a function of the peers’ contribution. By using a game theoretic framework, we analyze the interaction between a content provider’s rewarding strategy and the peers’ contributing behaviors and derive a unique Stackelberg equilibrium. We further analyze the system efficiency in terms of . Via extensive simulations, we validate the stability and efficiency of our incentive scheme.