Content Search Based On Thed Location And Interest In P2p Networks

As a revolutionary technology, P2P network is playing a significant role in the battlefield information networks. How to mass battlefield information that users need quickly and effectively, provide users with accurate and reliable real-time information services, provide real sharing of resources is urgently addressed. To meet the specific needs of information in battlefield P2P network, applying intelligent search method is a reasonable choice.In this paper, on the basis of the P2P network topology, analysis and research of existing search algorithm, a content search solution based on node location and user interest in a distributed unstructured P2P network under the battlefield environment is proposed, to improve the efficiency and precision of content searching. The main tasks include to improve the content search method based on node interest in the P2P network; propose a friends node choosing strategy using combination information of network node location and content correlation in the P2P network; design appropriate location information principles according to node IP information; propose a content correlation calculation method based on the node metadata content sharing degree for heterogeneous network data; suggest the friend network construction algorithm and the content search algorithm in the network on the basis of node-based location and active interest learning. Finally, performance analysis of the search solution is made and the simulation experiments show that the method proposed in this paper has a preferable search performance.