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Abstract
Aiming at the issue of low efficiency in Peer-to-Peer (P2P) network system, a search algorithm based on K-weighted search tree is proposed. The k-weighted search tree serving the search is constructed. The nodes are ranked from top to bottom in the tree according to the query hit rate, and the nodes with large hit rate and stable are on the tree layer, the search can thus determine the direction of the message diffusion. By caching the upper node, establishment of search results, using node index, overheated resource replication and add remote neighbours for leaf node, and other methods to improve search efficiency and balance load. The analysis and simulation results show that the proposed algorithm can greatly reduce the invalid message with higher search efficiency, and maintenance of the search tree is less expensive.
Highlights
Unstructured P2P network systems have been widely used with its simple structure, easy organization in large scale network resources sharing
We propose an unstructured P2P search model based on the K search tree
Analysis and simulation results show that we can significantly reduce the inefficient flow and increase search efficiency, and the search tree maintenance overhead is very small
Summary
Unstructured P2P network systems have been widely used with its simple structure, easy organization in large scale network resources sharing. Blind flood is the initial and basic search method for unstructured P2P, but overhead is too large, resulting in poor system scalability. Plane P2P structure is divided into multiple layers, the upper node management part of the lower nodes, and the same layer nodes connected each other. Such as KaZaA using super-section, to a certain extent, ease the flow problem, but the super-node may cause a single point of. The use of the establishment of search results historical index, and the search initiates a node index, caches the upper node, partially overrides the resource copy and is leaf nodes to increase the remote neighbors and other methods to further improve the search efficiency and balance negative contained. Analysis and simulation results show that we can significantly reduce the inefficient flow and increase search efficiency, and the search tree maintenance overhead is very small
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