• DocumentCode
    1901403
  • Title

    Cluster based approaches for end-to-end complete feedback collection in multicast

  • Author

    Baysan, Mehmet ; Sarac, Kamil

  • Author_Institution
    Dept. of Comput. Sci., Texas Univ., Dallas, TX
  • fYear
    2006
  • fDate
    10-12 April 2006
  • Lastpage
    38
  • Abstract
    In this paper we study the end-to-end complete feedback collection (ECFC) problem in large scale multi-cast applications. We consider the case where each receiver is expected to send feedback in a timely manner without causing implosion at the source site. To address the scalability problem and improve timely feedback collection, we introduce the use of clustering algorithms for feedback collection. Our simulation based comparisons show that the clustering based approaches outperform the existing pure (without clustering) multi-round probabilistic and pure (without clustering) delayed feedback collection approaches both in terms of collection delay and message overhead
  • Keywords
    feedback; multicast communication; pattern clustering; ECFC; clustering algorithm; end-to-end complete feedback collection problem; large scale multicast application; receiver; scalability; Application software; Clustering algorithms; Computer science; Feedback; IP networks; Large-scale systems; Multicast algorithms; Scalability; Streaming media; Web and internet services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Performance, Computing, and Communications Conference, 2006. IPCCC 2006. 25th IEEE International
  • Conference_Location
    Phoenix, AZ
  • Print_ISBN
    1-4244-0198-4
  • Type

    conf

  • DOI
    10.1109/.2006.1629387
  • Filename
    1629387