An Interest-Based Intelligent Link Selection Algorithm in Unstructured P2P Environment

Nowadays, most of the running P2P file sharing systems, such as Gnutella, generally adopt an unstructured topology and flooding search algorithms, which facing very serious search efficiency problem. In this paper, we proposed a novel intelligent link selection algorithm to address the search efficiency problem by exploiting the principle of interest-based locality. Specifically, peers continually build new connections with the others peers with same interests, this enables peers find its interest files in the nearby ones. In addition, in order to avoid adding too many connections in the overlay network which may lead the flooding search produce excessive redundant message as a consequence, we adopt a dynamic balance mechanism to delete the connection between peers which brings the least useful message. The simulation study shows our algorithm can significantly cut down the reply path lengths, achieve high search success rate with smaller search scope, and reduce the total communication cost in unstructured P2P systems.