socP2P: P2P content discovery enhancement by considering social networks characteristics

Content management appears as an essential requirement in order to deploy enhanced P2P networks. In P2P networks, the content that is requested by the query node could be located at different locations/nodes; therefore an efficient search mechanism is required. The proposed search algorithm in this paper, called socP2P, relies on peers' social relationships (friendships, shared interests, shared background and experiences) to improve the content discovery compared to similar solutions. With socP2P nodes can improve searches by using knowledge gained by `overheard information' during their stay in the network. In addition, our algorithm exploits peers' common interests, friendships, and capability of memorizing experiences (received and routed queries) by them. Simulation results show that socP2P is able to achieve a high success rate, low delay and low overhead. We have verified that our algorithm is not only useful in finding popular contents in the network but also good enough to locate rare files. The obtained results reflect that exploiting social information in P2P networks leads to a more efficient content search mechanism.