CATS: A topology construction based on semantic group for Capacity-Aware in heterogeneous P2P networks

Search efficiency and accuracy of resource are important considerations in P2P networks. Most researches focus on improving search efficiency through efficient search mechanisms. However, they ignore the impact of P2P network topology on search efficiency, especially in heterogeneous network environments. In this paper, we propose a novel semantic topology construction method CATS (Capacity-Aware Topology based on Semantic) based on Vector Space Model (VSM). This topology construction method considers node capacity based on semantic in heterogeneous environment. Through building a rational and effective semantic topology, it significantly improves the search efficiency. Meanwhile, we adopt a novel and efficient search mechanism BF-SKTP (Biased walk, Flooding and Search with K-Iteration Preference) to promote searching within network. Compared with the current homogeneous semantic-based topology construction method GES, CATS outperform GES in terms of higher recall and lower search cost.