• DocumentCode
    2767646
  • Title

    Keynote 5: Exploiting social metrics in content distribution

  • Author

    Stavrakakis, Ioannis

  • Author_Institution
    Dept. of Inf. & Telecommun., Nat. Kapodistrian Univ. of Athens, Athens, Greece
  • fYear
    2011
  • fDate
    June 28 2011-July 1 2011
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Summary form only given. Social metrics have recently been considered to capture the degree of similarity in interests of the nodes as well as their “standing” within a community or network. In this talk some recent works-examples are briefly presented showing the potential benefits from incorporating social metrics in content replication, forwarding and placement. More specifically, a framework for assessing interest similarity is presented and applied to illustrate how similarity affects the effectiveness of content replication and forwarding. In addition, the widely adopted Betweenness Centrality metric is revisited and issues associated with its computation and appropriateness for content forwarding are discussed. Then, modifications and easily computable variants are introduced and their effectiveness is illustrated.
  • Keywords
    social networking (online); betweenness centrality metric; content distribution; content forwarding; content placement; content replication; social metrics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers and Communications (ISCC), 2011 IEEE Symposium on
  • Conference_Location
    Kerkyra
  • ISSN
    1530-1346
  • Print_ISBN
    978-1-4577-0680-6
  • Electronic_ISBN
    1530-1346
  • Type

    conf

  • DOI
    10.1109/ISCC.2011.5984770
  • Filename
    5984770