• DocumentCode
    2657916
  • Title

    Data Scheduling Strategy in P2P VoD System Based on Genetic Algorithm

  • Author

    Huang, Guimin ; Li, Changliang ; Zhou, Ya ; Bin, Chenzhong

  • Author_Institution
    Guilin Univ. of Electron. Technol., Guilin, China
  • fYear
    2011
  • fDate
    4-6 Nov. 2011
  • Firstpage
    128
  • Lastpage
    131
  • Abstract
    In P2P (Peer-to-Peer) VoD (Video-on-Demand) System, data scheduling strategy is critical to make full use of node resource in P2P network, and it can help optimize user experience as well as system throughput. But for a normal peer how to efficiently schedule media data still remains a challenging task. The kind of problem is NP-hard problem due to the dynamic characteristics of P2P network. This paper presents a novel data scheduling strategy for resolving this problem, called GA scheduling, the major characteristic of which is to adopt genetic algorithm for optimization. Four steps (selection/ crossover/ mutation/ evaluation) are applied iteratively to optimize scheduling effect until stopping condition is met. Several experiments are designed at last on the P2P VoD system. The results demonstrate the effectiveness of the data scheduling strategy proposed in this paper.
  • Keywords
    data handling; genetic algorithms; peer-to-peer computing; scheduling; video on demand; GA scheduling; NP-hard problem; P2P VoD system; P2P network; data scheduling; data scheduling strategy; genetic algorithm; peer-to-peer system; video-on-demand system; Delay; Genetic algorithms; Media; Peer to peer computing; Scheduling; Servers; Video recording; NP-hard problem; P2P VoD System; data scheduling strategy; genetic algorithm; node resource;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Information Networking and Security (MINES), 2011 Third International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4577-1795-6
  • Type

    conf

  • DOI
    10.1109/MINES.2011.86
  • Filename
    6103737