Indexing range sum queries in spatio-temporal databases

Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the historical records of moving objects despite their importance. Since the direct access to a huge amount of data to answer range sum queries incurs prohibitive computation cost, materialization techniques based on existing index structures are suggested. A simple but effective solution is to apply the materialization technique to the MVR-tree known as the most efficient structure for window queries with spatio-temporal conditions. Aggregate structures based on other index structures such as the HR-tree and the 3DR-tree do not provide satisfactory query performance. In this paper, we propose a new index structure called the Adaptively Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently process range sum queries in many situations. Our experimental results show that the performance of the APART is typically 1.3 times better than that of its competitor for a wide range of scenarios. (c) 2006 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2007-04
Language
ENG
Keywords

AGGREGATION

Citation

INFORMATION AND SOFTWARE TECHNOLOGY, v.49, no.4, pp.324 - 331

ISSN
0950-5849
DOI
10.1016/j.infsof.2006.05.005
URI
http://hdl.handle.net/10203/1920
Appears in Collection
CS-Journal Papers(저널논문)
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