document: Information retrieval in P2P networks using genetic algorithm Hybrid Peer-to-Peer ( P2P ) networks based on the direct connection model have two shortcomings which are high bandwidth consumption and poor semi-parallel search . However , they can further be improved by the query propagation model . In this paper , we propose a novel query routing strategy called GAroute based on the query propagation model . By giving the current P2P network topology and relevance level of each peer , GAroute returns a list of query routing paths that cover as many relevant peers as possible . We model this as the Longest Path Problem in a directed graph which is NP-complete and we obtain high quality ( 0.95 in 100 peers ) approximate solutions in polynomial time by using Genetic Algorithm ( GA ) . We describe the problem modeling and proposed GA for finding long paths . Finally , we summarize the experimental results which measure the scalability and quality of different searching algorithms . According to these results , GAroute works well in some large scaled P2P networks .
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