Reasearch On Unstructured P2P Searching Tecnology Based On Ant Colony Algorithm

Peer-to-peer(P2P) network has become an important application in Internet. P2P network collects the resource on the nodes at the edge of Internet to provide strong computing power and storage capability. Because of its flexibility on query pattern and adaptability to dynamic environment, unstructured P2P network is widely deployed and become the mainstream of the current P2P networks. However, unstructured P2P networks suffer from poor performance, therefore improving searching algorithm is one important major research area for unstructured P2P network. Unfortunately, existing P2P searching mechanisms are usually dissatisfied. For example, structured P2P systems are efficient but lack of actual implements on the Internet, because of their complicated structures. Unstructured P2P systems are inefficient but more popular.From various perspectives, our work focuses on how to improve retrieval efficiency of unstructured P2P file-sharing systems. In this paper, we present a new approach to P2P information retrieval—ACODA, using ant colony algorithm to solve the problem such as huge message packets, low search efficiency, redundancy routes and others. The algorithm simulates the process of the ants'searching food and can direct the query routing efficiently according to the positive feedback principle of the ant pheromone. It sends the query messages to the area where there could be the requested resources to improve the search efficiency.Besides, information recommendation services based on ACODA is introduced in paper. The peer transfers information periodically to other peers according to their interest. By this method it can raise the file-sharing level and reduce blind searches. A verify-renascence method is provided in paper to improve the performance of index caching. This method can efficiently solve the invalid indices problem and its'expansion problem. It can improve the search efficiency by increasing the life time of the valid index.The simulation based on PeerSim software shows, the information retrieve strategy of ACODA algorithm with information recommendation services and index caching can efficiently reduce the time of finding the resources. It can achieve a better search performance and low the network loads by increasing the resource hit ratio and reducing the query message packets of redundancy.