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
Link To Document