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MR-tree with Voronoi Diagrams for Parallel Spatial Queries

FU Zhongliang

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Abstract

Spatial indices are used by spatial databases to optimize spatial queries.We introduce a parallel spatial range query algorithm based on VoMR-tree index.The MR-tree is firstly augmented to store the nearest neighbors and constructs the Voronoi diagram.Then a range query algorithm based on VoMR-tree index is proposed.In processing a range query,the data partition method so that can improve the efficiency by parallelization in distributed database is discussed.The experimental results show that the proposed method improves the performance of range query processing in comparison with the widely-used methods.

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What this paper is about

Spatial indices are used by spatial databases to optimize spatial queries.We introduce a parallel spatial range query algorithm based on VoMR-tree index.The MR-tree is firstly augmented to store the nearest neighbors and constructs the Voronoi diagram.Then a range query algorithm based on VoMR-tree index is proposed.In processing a range query,the data partition method so that can improve the efficiency by parallelization in distributed database is discussed.The experimental results show that the proposed method improves the performance of range query processing in comparison with the widely-used methods.

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Available abstract

Spatial indices are used by spatial databases to optimize spatial queries.We introduce a parallel spatial range query algorithm based on VoMR-tree index.The MR-tree is firstly augmented to store the nearest neighbors and constructs the Voronoi diagram.Then a range query algorithm based on VoMR-tree index is proposed.In processing a range query,the data partition method so that can improve the efficiency by parallelization in distributed database is discussed.The experimental results show that the proposed method improves the performance of range query processing in comparison with the widely-used methods.

Key concepts: Voronoi diagram, Spatial query, Computer science, Range query (database), Spatial database, Partition (number theory), Range (aeronautics), Data mining

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