Resource Search Algorithm In Unstructured P2P Network

Peer-to-peer network has been used widely in resource sharing, multimedia transmission and distributed collaboration as a new network model. The resources are distributed in each peer of the P2P network, which has amount of information, and nodes can share resource and exchange information with each other. A valid searching resource mechanism could ensure that users in the P2P network quickly and accurately search to the resources needed in the conditions of the small system overhead that improve the user experience satisfaction. Therefore, how to quickly search result from a lot of network resources is becoming one of the key issues in the P2P network.This paper describes the background of the subject and research status at home and abroad of P2P network, analysis the searching algorithm in unstructured P2P network and summarize improvement strategies about unstructured P2P network resource search algorithm. To solve the problems of low efficiency and more redundant messages in unstructured P2P network resources search, an ant colony resources search algorithm based on interest factor (IACO) is proposed. This algorithm gives full consideration to the effects of node value of resources search. Node interest factor is introduced into traditional ant colony algorithm to adjust the weight relationship of node value and pheromones dynamically in the transmitting probability calculation and effectively guide the generation of resources query path. And to solve the problems of the low successful rate of the searching scarce resources in the network, the paper presents a searching scarce resource strategy based on the IACO algorithm. The policy could determine the scarce resources of the network through a detection method about scarce resources and backup the scarce resources in the routing nodes of the IACO which is determined by node value and the pheromone. Through this method, we can improve the network sharing of the scarce resources and improve the successful rate of the scarce resources of the IACO algorithm search.Finally, the article verifies the IACO algorithm and scarce resources search strategy. We prove the algorithm from successful rate of the resource discovery and the number of messages in the network in the Gnutella network environment simulated by peersim, and has verified the feasibility and effectiveness of the algorithm.