
Unstructured peer-to-peer (P2P) networks suffer from the increased volume of traffic produced by flooding. Methods such as random walks or dynamic querying managed to limit the traffic at the cost of reduced network coverage. In this paper, we propose a partitioning method of the unstructured overlay network into a relative small number of distinct subnetworks. The partitioning is driven by the categorization of keywords based on a uniform hash function. The method proposed in this paper is easy to implement and results in significant benefit for the blind flood method. Each search is restricted to a certain partition of the initial overlay network and as a result it is much more targeted. Last but not least, the search accuracy is not sacrificed to the least since all related content is searched. The benefit of the proposed method is demonstrated with extensive simulation results, which show that the overhead for the implementation and maintenance of this system is minimal compared to the resulted benefit in traffic reduction.
Unstructured peer to peers, Overlay networks, Sub-networks, Related contents, Network coverages, Overlay network, Unstructured peer-to-peer systems, Search accuracies, Unstructured overlay networks, Extensive simulations, Flooding, Peer-to-peer, Traffic reductions, Client server computer systems, Resource location, Partitioning methods, Random walks
Unstructured peer to peers, Overlay networks, Sub-networks, Related contents, Network coverages, Overlay network, Unstructured peer-to-peer systems, Search accuracies, Unstructured overlay networks, Extensive simulations, Flooding, Peer-to-peer, Traffic reductions, Client server computer systems, Resource location, Partitioning methods, Random walks
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