Assisted peer-to-peer search with partial indexing

Abstract

This paper proposes to improve search in unstructured peer-to-peer (P2P) overlay networks by building a partial index of shared data. The index maintains two types of information: the top interests of peers and globally unpopular data, both characterized by data properties. The proposed search protocol, assisted search with partial indexing, makes use of the index to improve search in three ways. First, the index assists peers to find other peers with similar interests and the unstructured search overlay is formed to reflect peer interests. Second, the index also provides search hints for those data difficult to locate by exploring peer interest locality, and these hints can be used for second-chance search. Third, the index helps to locate unpopular data items. Experiments based on both the Web and P2P file sharing traces show that the assisted search with a lightweight partial indexing service can significantly improve the success rate and search speed in locating data, while inducing less traffic overhead than Gnutella and a hit-rate based protocol in unstructured P2P systems.