A Triangular Decomposition Access Method for Temporal Data - TD-tree
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Author(s)
Stantic, B
Topor, R
Terry, J
Sattar, A
Year published
2011
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In this study, we investigate and present a new index structure, Triangular Decomposition Tree (TDtree), which can efficiently store and query temporal data in modern database applications. TD-tree is based on spatial representation of interval data and a recursive triangular decomposition of this space. A bounded number of intervals are stored in each leaf of the tree, which hence may be unbalanced. We describe the algorithms used with this structure. A single query algorithm can be applied uniformly to different query types without the need of dedicated query transformation. In addition to the advantages related ...
View more >In this study, we investigate and present a new index structure, Triangular Decomposition Tree (TDtree), which can efficiently store and query temporal data in modern database applications. TD-tree is based on spatial representation of interval data and a recursive triangular decomposition of this space. A bounded number of intervals are stored in each leaf of the tree, which hence may be unbalanced. We describe the algorithms used with this structure. A single query algorithm can be applied uniformly to different query types without the need of dedicated query transformation. In addition to the advantages related to the usage of a single query algorithm for different query types and better space complexity, the empirical performance of the TD-tree is demonstrated to be superior to its best known competitors. Also, presented concept can be extended to more dimensions and therefore applied to efficiently manage spatio-temporal data.
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View more >In this study, we investigate and present a new index structure, Triangular Decomposition Tree (TDtree), which can efficiently store and query temporal data in modern database applications. TD-tree is based on spatial representation of interval data and a recursive triangular decomposition of this space. A bounded number of intervals are stored in each leaf of the tree, which hence may be unbalanced. We describe the algorithms used with this structure. A single query algorithm can be applied uniformly to different query types without the need of dedicated query transformation. In addition to the advantages related to the usage of a single query algorithm for different query types and better space complexity, the empirical performance of the TD-tree is demonstrated to be superior to its best known competitors. Also, presented concept can be extended to more dimensions and therefore applied to efficiently manage spatio-temporal data.
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Conference Title
Conferences in Research and Practice in Information Technology Series
Volume
115
Copyright Statement
© 2011 Australian Computer Society Inc. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
Subject
Data structures and algorithms