SSW: A small-world-based overlay for peer-to-peer search

Peer-to-peer (P2P) systems have become a popular platform for sharing and exchanging voluminous information among thousands or even millions of users. The massive amount of information shared in such systems mandates efficient semantic based search instead of key-based search. This paper presents the design of an overlay network, namely semantic small world (SSW), that facilitates efficient semantic based search in P2P systems. SSW achieves the efficiency based on the following four ideas: 1) semantic clustering: peers with similar semantics organize into peer clusters; 2) dimension reduction: to address the high maintenance overhead associated with capturing high-dimensional data semantics in the overlay, peer clusters are adaptively mapped to a one-dimensional naming space; 3) small world network: peer clusters form into a one-dimensional small world network, which is search efficient with low maintenance overhead; 4) efficient search algorithms: peers perform efficient semantic based search, including approximate point query and range query, in the proposed overlay. Extensive experiments using both synthetic data and real data demonstrate that SSW is superior to the state-of-the-art on various aspects, including scalability, maintenance overhead, adaptivity to distribution of data and locality of interest, resilience to peer failures, load balancing, and efficiency in support of various types of queries on data objects with high dimensions.