Distributed social-based overlay adaptation for unstructured P2P networks

Ching-Ju Lin*, Yi Ting Chang, Shuo Chan Tsai, Cheng Fu Chou

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations


The widespread use of Peer-to-Peer (P2P) systems has made multimedia content sharing more efficient. Users in a P2P network can query and download objects based on their preference for specific types of multimedia content. However, most P2P systems only construct the overlay architecture according to physical network constraints and do not take user preferences into account. In this paper, we investigate a social-based overlay that can cluster peers that have similar preferences. To construct a semantic social-based overlay, we model a quantifiable measure of similarity between peers so that those with a higher degree of similarity can be connected by shorter paths. Hence, peers can locate objects of interest from their overlay neighbors, i.e., peers who have common interests. In addition, we propose an overlay adaptation algorithm that allows the overlay to adapt to P2P churn and preference changes in a distributed manner. We use simulations and a real database called Audioscrobbler, which tracks users' listening habits, to evaluate the proposed social-based overlay. The results show that social-based overlay adaptation enables users to locate content of interest with a higher success ratio and with less message overhead.

Original languageEnglish
Title of host publication2007 IEEE Global Internet Symposium, GI
Number of pages6
StatePublished - 1 Dec 2007
Event2007 IEEE Global Internet Symposium, GI - Anchorage, AK, United States
Duration: 11 May 200711 May 2007

Publication series

Name2007 IEEE Global Internet Symposium, GI


Conference2007 IEEE Global Internet Symposium, GI
CountryUnited States
CityAnchorage, AK

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