The Research On Searching Algorithm In Monitoring And Analysis Of P2P Stream Media

In nowadays, with the quick development of internet techniques, it has come into the time of information society. P2 P techniques, which have the characteristic concept of “equality, sharing” as well as “no-center”, brought the reasonable deployment of network resources and high-speed development of P2 P techniques utilities. During the development of P2 P network, most quickly of all is P2 P stream media. In nowadays, the point-to-point network almost reach everywhere of each computer all over the world. There are also a lot of legal problems, such as copyrights and flood of harmful information.In order to solve these problems, on basis of present existing mechanisms, web-crawleralgorithm were designed not only through the comparison of nodes modulation the incentive mechanism,but also through the analysis of the most popular topologies andprotocols Ed2 k and KAD in P2 P internet. A targeted search program was thus proposed to meet the numerous needs of P2 P internet monitoring. Statistical results were brought according to the request of monitoring and analysis, thus a network monitoring and analysis model was discussed on basis of above two P2 P network Ed2 k and KAD.Finding is the first problem to be solved in P2 P internet monitoring. In order to solve this problem, a key word searching algorithm for Ed2 k network and KAD network was designed in the thesis, thus keyword searching function was realized in Ed2 k index server and KAD net-nodes worldwide.In order to improve the efficiency of internet searching, a searching program that combined high-frequency searching and low-frequency searching was proposed. Through the former high-frequency searching, a quick keyword searching for above two P2 P network was realized. And through the latter low-frequency searching, a deeper excavation was realized for P2 P network users in sharing files and other information through internet.In the end, the most popular P2 P e Mule network was chosen for our P2 P network monitoring in data testing, analysis and comparison. As a result, it met the needs of searching algorithm and worked well.