unstructured p2p networks

SocioNet: A Social-Based Multimedia Access System for Unstructured P2P Networks

PEER-TO-PEER (P2P) systems have become one of the most popular distributed applications on the Internet today. Increasingly, peer-to-peer (P2P) network users expect to be able to search objects by semantic attributes based on their preferences for multimedia content. Partial match search (i.e., search through the use of multimedia content semantic information), has become an essential service in P2P systems. In this project, we propose SocioNet, a social-based overlay that clusters peers based on their preference relationships as a small world network. In SocioNet, peers imitates how people form a social network and how they query, by preference, their friends or acquaintances. Hence, SocioNet benefits from two desirable features of a social network: interest-based clustering and small-world properties (i.e., high cluster coefficient among all peers yet short path lengths between any two peers). To realize an interest-based small-world SocioNet, we also investigate the following practical design issues: 1) similarity estimation: we define a quantifiable similarity measure that enables clustering of similar peers in SocioNet, 2) Distributed small-world overlay adaptation: peers maintain a small-world overlay under network dynamics, and 3) query strategy under the small-world overlay: we analyze appropriate settings for the Time-to-Live (TTL) value, for TTL-limited flooding, that provides a satisfactory success ratio and avoids redundant message overhead.
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