Peer-to-peer unstructured anycasting using correlated swarms

Pushkar Patankar, Gunwoo Nam, George Kesidis, Panagiotis Takis Konstantopoulos, Chita R. Das

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Over the recent years, social network analysis has received renewed interest because of the significant increase in the number of users relying on applications based on them. An important criterion for the success of any social-networking based application is the efficiency of search. In this paper, we propose and analyze a method of anycast search based on correlated communities or subgroups, i.e., using group-to-group caching. It works by restricting search to peers that belong to communities which are highly correlated with the requested community. We analytically prove that our proposed method works better than basic random walk, which remains a widely used method for performing search in these networks. Indeed our experiments prove that the proposed method reduces the search time by as much as 30% to that based on random walk. Our experiments also indicate that the proposed method outperforms basic random walk even under considerable peer-churn.

Original languageEnglish
Title of host publication21st International Teletraffic Congress, ITC 21: Traffic and Performance Issues in Networks of the Future - Final Programme
Publication statusPublished - 2009
Event21st International Teletraffic Congress, ITC 21: Traffic and Performance Issues in Networks of the Future - Final Programme - Paris, France
Duration: 15 Sep 200917 Sep 2009

Conference

Conference21st International Teletraffic Congress, ITC 21: Traffic and Performance Issues in Networks of the Future - Final Programme
CountryFrance
CityParis
Period15/09/0917/09/09

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