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The B dual -Tree: indexing moving objects by space filling curves in the dual space

The B dual -Tree: indexing moving objects by space filling curves in the dual space Existing spatiotemporal indexes suffer from either large update cost or poor query performance, except for the B x -tree (the state-of-the-art), which consists of multiple B + -trees indexing the 1D values transformed from the (multi-dimensional) moving objects based on a space filling curve (Hilbert, in particular). This curve, however, does not consider object velocities, and as a result, query processing with a B x -tree retrieves a large number of false hits, which seriously compromises its efficiency. It is natural to wonder “can we obtain better performance by capturing also the velocity information, using a Hilbert curve of a higher dimensionality?”. This paper provides a positive answer by developing the B dual -tree, a novel spatiotemporal access method leveraging pure relational methodology. We show, with theoretical evidence, that the B dual -tree indeed outperforms the B x -tree in most circum- stances. Furthermore, our technique can effectively answer progressive spatiotemporal queries, which are poorly supported by B x -trees. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

The B dual -Tree: indexing moving objects by space filling curves in the dual space

Yiu, Man; Tao, Yufei; Mamoulis, Nikos
The VLDB Journal , Volume 17 (3) – May 1, 2008
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References (23)

Publisher
Springer Journals
Copyright
Copyright © 2008 by Springer-Verlag
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
DOI
10.1007/s00778-006-0013-2
Publisher site
See Article on Publisher Site

Abstract

Existing spatiotemporal indexes suffer from either large update cost or poor query performance, except for the B x -tree (the state-of-the-art), which consists of multiple B + -trees indexing the 1D values transformed from the (multi-dimensional) moving objects based on a space filling curve (Hilbert, in particular). This curve, however, does not consider object velocities, and as a result, query processing with a B x -tree retrieves a large number of false hits, which seriously compromises its efficiency. It is natural to wonder “can we obtain better performance by capturing also the velocity information, using a Hilbert curve of a higher dimensionality?”. This paper provides a positive answer by developing the B dual -tree, a novel spatiotemporal access method leveraging pure relational methodology. We show, with theoretical evidence, that the B dual -tree indeed outperforms the B x -tree in most circum- stances. Furthermore, our technique can effectively answer progressive spatiotemporal queries, which are poorly supported by B x -trees.

Journal

The VLDB Journal – Springer Journals

Published: May 1, 2008

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