Dynamic Super-Peer Network Model And Search Algorithm Based On Semantics

As a new network compute mode, P2P(peer-to-peer) network modifies the traditional C/S mode and has been used more and more popularity. The information amount rose rapidly with the intense increment of both users' quantity and network's scale and caused a serious problem, difficulty in searching, locating and retrieving resource. To conquer this problem, information retrieval in P2P network is a pivotal technique. A good strategy not only increases hit ratio and decreases node load and network cost, but also serves for users in studying relevant information to improve the performance in later search process and save time.For using broadcasting as its basic search strategy in unstructured P2P networks now, a larger network flows are caused. So, an improved search approach based on semantic is proposed. Based on relational interests between peers, introduce friend-nodes to each peer, and gradually gather nodes with the same interest. Then divide nodes into two types: super-nodes in logic and ordinary-nodes while gathering. Update the friend-nodes' information making use of the successful searches. So reduce the frequency of the cached nodes' replacement and update super-nodes' information in logic. As a result, the search extension is reduced and the search efficiency is improved. Simulation results show that improved methods enhance the search efficiency and reduce the network costs.Model analysis and simulation results prove that, the interest-based search mechanism is more efficient than the traditional search method in Gnutella-like system.