Query statistic-based guidance searching method for P2P system

Abstract

The invention discloses a query statistic-based guidance searching method for a P2P system. The method comprises the following steps: (1) establishing a statistic guidance table SGT; establishing a 'statistic guidance table' with a double layer structure based on history query statistics and semantic analysis results, wherein only a history queried currently is saved in an upstream table entry, and is ranked according to query time; and node information and advantage factors which respond to the current query or similar query are saved in an downstream table entry; (2) querying files by usingthe statistic guidance table, and performing querying by using information in the SGT according to the semantic dependency of the current query and SGT history query after the statistic guidance table is established by nodes; automatically starting an underlying query strategy if the history saved in the SGT has little dependency with the current query; and (3) adaptively updating the statistic guidance table, including two methods, namely active updating and passive updating, wherein the passive mode takes place after the node forwards a query request.

Description

1. Technical field [0001] The present invention designs a general query enhancement method for P2P networks. The method is independent of the underlying topological structure, and uses historical query statistics and semantic analysis results to guide each query request to the node most likely to provide corresponding information. Its use effectively reduces the network overhead of queries, improves the success rate of queries, reduces communication delays, and hardly increases additional maintenance overhead. 2. Background technology [0002] So far, there have been many classic query methods, such as server-based query methods in hybrid P2P networks; flooding methods, random walk methods, extended ring methods, super-node methods, etc. in unstructured P2P networks; Under the structured P2P model, the DHT-based value proximity method, position proximity method, bit-by-bit matching method, etc. However, we found that in practical applications, various models are limited due...

AI Technical Summary

Problems solved by technology

However, we found that in practical applications, various models are limited due to their own defects, and the unstructured P2P network has become the mainstream P2P practical system due to the advantages of simple topology and strong fault tolerance, but some of the unstructured P2P network itself The disadvantages limit its better expansion and operation. The biggest problem is the contradiction between data query success rate and query overhead

The network overhead caused by the traditional flooding query is too large, and the query methods such as random walk and extended ring with low overhead cannot guarantee the success rate of the query

Images