Scalable Search based on Fuzzy Clustering for Interest-based P2P Networks

An interest-based P2P constructs the peer connections based on similarities for efficient search of resources. A clustering technique using peer similarities as data is an effective approach to group the most relevant peers. However, the separation of groups produced from clustering lowers the scalability of a P2P network. Moreover, the interest-based approach is only concerned with user-level grouping where topology-awareness on the physical network is not considered. This paper proposes an efficient scalable search for the interest-based P2P system. A scalable multi-ring (SMR) based on fuzzy clustering handles the grouping of relevant peers and the proposed scalable search utilizes the SMR for scalability of peer queries. In forming the multi-ring, a minimized route function is used to determine the shortest route to connect peers on the physical network. Performance evaluation showed that the SMR acquired an accurate peer grouping and improved the connectivity rate of the P2P network. Also, the proposed scalable search was efficient in finding more replicated files throughout the peer network compared to other traditional P2P approaches.