Research on Searching in Unstructured P2P Network Based on Power-Law Distribution and Small World Character

Unstructured peer-to-peer (P2P) systems have been widely used in the Internet. The common search method used is flooding-based broadcasting. This method usually leads to serious communication cost problem. Based on the observation and analysis of social communication network, it is noticed that in social communication network, the transfer of message is optimized. In message spreading, reduplicate communication cost is avoid unwillingly. The rumor spreading mechanism utilizes the clustering characteristic of social communication network in born. The mechanism responsible for the emergence of power-law networks is growth and preferential attachment. In this paper, based on the power-law distribution and small world character of unstructured P2P networks, a search method is presented. This method combines preference link mechanism, which generates the power-law character, and interest decline mechanism in rumor spreading, which is accommodated to clustering network. Mathematical analyses show that this approach could sharply optimize the communication cost in P2P systems. To evaluate the effectiveness of this algorithm, using topology generation tool BRITE to generate simulation network based on the GLP (generalized linear preference) model. The result of the preliminary simulation shows that the communication cost of this algorithm is less than the half of the flooding algorithm, and the overlay degree of this algorithm is quite high.