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A Vomr-tree Based Parallel Range Query Method on Distributed Spatial Database : Volume I-2, Issue 1 (11/07/2012)

By Fu, Z.

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Book Id: WPLBN0004013560
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: A Vomr-tree Based Parallel Range Query Method on Distributed Spatial Database : Volume I-2, Issue 1 (11/07/2012)  
Author: Fu, Z.
Volume: Vol. I-2, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2012
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Liu, S., & Fu, Z. (2012). A Vomr-tree Based Parallel Range Query Method on Distributed Spatial Database : Volume I-2, Issue 1 (11/07/2012). Retrieved from http://ebook2.worldlibrary.net/


Description
Description: School of Remote and Sensing , Wuhan University, Wuhan, China. Spatial index impacts upon the efficiency of spatial query seriously in distributed spatial database. In this paper, we introduce a parallel spatial range query algorithm, based on VoMR-tree index, which incorporates Voronoi diagrams into MR-tree, benefiting from the nearest neighbors. We first augments MR-tree to store the nearest neighbors and constructs the VoMR-tree index by Voronoi diagram. We then propose a novel range query algorithm based on VoMR-tree index. In processing a range query, we discuss the data partition method so that we can improve the efficiency by parallelization in distributed database. Just then a verification strategy is promoted. We show the superiority of the proposed method by extensive experiments using data sets of various sizes. The experimental results reveal that the proposed method improves the performance of range query processing up to three times in comparison with the widely-used R-tree variants.

Summary
A VOMR-TREE BASED PARALLEL RANGE QUERY METHOD ON DISTRIBUTED SPATIAL DATABASE

 

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