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 :
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