• DocumentCode
    491678
  • Title

    A novel substream extraction for Scalable Video Coding over P2P networks

  • Author

    Li, Chunhua ; Yuan, Chun ; Zhong, Yuzhuo

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing
  • Volume
    03
  • fYear
    2009
  • fDate
    15-18 Feb. 2009
  • Firstpage
    1611
  • Lastpage
    1615
  • Abstract
    Video distribution through peer-to-peer (P2P) networks using Scalable Video Coding (SVC) has been an active research. And bitstream extraction is an important issue in SVC transmission. In this paper, we propose a global optimal GOP-adaptive Rate-Distortion optimization extraction algorithm for SVC streaming multicasting over P2P networks. This method solves the problem of serving many clients with heterogeneous bandwidth, and it makes the transmission more efficient and robust under the same bandwidth condition. The algorithm has been implemented with JSVM 11, and simulations are performed to verify the proposed scheme using NS-2. Experiment results show that the proposed algorithm not only offers better performance but also doesn´t bring too much computation costs as compared with existing methods.
  • Keywords
    peer-to-peer computing; rate distortion theory; video coding; video streaming; JSVM 11; NS-2; P2P Networks; bitstream extraction; global optimal GOP-adaptive rate-distortion optimization extraction algorithm; heterogeneous bandwidth; peer-to-peer networks; scalable video coding; substream extraction; video distribution; Bandwidth; Computational efficiency; Computational modeling; Multicast algorithms; Peer to peer computing; Rate-distortion; Robustness; Static VAr compensators; Streaming media; Video coding; Peer-to-Peer; Rate-Distortion Optimization; Scalable Video Coding; Substream Extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Technology, 2009. ICACT 2009. 11th International Conference on
  • Conference_Location
    Phoenix Park
  • ISSN
    1738-9445
  • Print_ISBN
    978-89-5519-138-7
  • Electronic_ISBN
    1738-9445
  • Type

    conf

  • Filename
    4809381