• DocumentCode
    588934
  • Title

    An Improved Classification Method of Unstructured P2P Multicast Video Streaming

  • Author

    Chaobin Liu ; Qiang Guo ; Jie He

  • Author_Institution
    Inf. Center, Second Mil. Med. Univ., Shanghai, China
  • Volume
    2
  • fYear
    2012
  • fDate
    28-29 Oct. 2012
  • Firstpage
    415
  • Lastpage
    418
  • Abstract
    The classification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. Based on the classification method in the preliminary research, an improved classification method is proposed. the method uses an optimal feature vector extraction algorithm to filter the proposed behavior features in the original method, which greatly lower the feature vector dimension. an improved multi-class support vector machines is also used in the improved method, which not only solves the problem of rejecting sub-regional, but also reduces the computational complexity and improves the identification accuracy. Experiments show that the improved method has less computational and storage overhead, and has higher identification accuracy.
  • Keywords
    computational complexity; multicast communication; peer-to-peer computing; support vector machines; video streaming; classification method; computational complexity; multiclass support vector machines; network monitoring management; online linkage; optimal feature vector extraction algorithm; real-time evidence; unstructured P2P multicast video streaming; Accuracy; Binary trees; Feature extraction; Streaming media; Support vector machine classification; Vectors; classification; improved method; unstructured P2P multicast video streaming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-2646-9
  • Type

    conf

  • DOI
    10.1109/ISCID.2012.259
  • Filename
    6406027