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Distributed Hash Table (DHT) is a promising approach for a distributed data management platform in a large-scale network environment. In order to provide an efficient query processing and resource sharing in information discovery services, any DHT-based P2P system essent ially needs to build an efficient indexing scheme for supporting users’ desired queries (complex query, i.e., multi-dimensi onal and/or range query). In this paper, multi-dimensional indexing scheme is built by generating multi-dimensional keys. For this purpose, k-dimensional tree (kd-tree) is proposed to be used in the indexing scheme. This paper focuses on the performan ce of kd-tree regarding to its splitting threshold value and evaluates it by using three metrics: (1) number of empty nodes o n tree (2) number peers with data size zero, and (3) number of wrong labels. According to the simulated results, this pa per defines that kd-tree is built at the splitting threshold value “200” and builds a multi-dimensional indexing scheme over Chord. This paper shows that how the proposed indexing scheme with th e usage of kd-tree supports the complex query processing over Chord.

Usage of Kd-Tree in DHT-Based Indexing Scheme