Browse > Article

A Hybrid Index based on Aggregation R-tree for Spatio-Temporal Aggregation  

You, Byeong-Seob (인하대학교 컴퓨터.정보공학과)
Bae, Hae-Young (인하대학교 컴퓨터.정보공학과)
Publication Information
Journal of KIISE:Databases / v.33, no.5, 2006 , pp. 463-475 More about this Journal
Abstract
In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.
Keywords
Spatial Data Warehouse; Decision support; Spatio-Temporal Index;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. A. Finkel, and J. L. Bentley, 'Quad trees: A data structure for retrieval on composite keys,' Acta Informatica, Vol. 4, pp. 1-9 1974   DOI
2 N. Beckmann, H. P. Kriegel, R. Schneider, and B. Seeger, 'The R*-tree: an efficient and robust access method for points and rectangles,' ACM SIGMOD, vol. 19, No.2, pp. 322-331 1990   DOI
3 I.S. Mumick, D. Quass, and B.S. Mumick. 'Maintenance of data cubes and summary tables in a warehouse,' In Proc. of ACM SIGMOD, Vo1.26, No.2, pp. 100-111, 1997   DOI   ScienceOn
4 Eric Sperley, The Enterprise Data Warehouse: Planning, Building, and Implementation, Prentice Hall PTR, pp. 8-15, 1999
5 N. Stefanovic, J. Han, and K. Koperski, 'Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes,' IEEE Transactions on Knowledge and Data Engineering, vol. 12(6), pp. 1-21, 2000   DOI   ScienceOn
6 T. K. Sellis, N. Roussopoulos, and C. Faloutsos, 'The R+-Tree: A dynamic index for multidimensional objects,' VLDB, 1987
7 A. Guttman, 'R-trees: a dynamic index structure for spatial searching,' ACM SIGMOD, Vo1.14, No.2, pp. 47-57, 1984   DOI
8 Y. Tao and D. Papadias, 'Range Aggregate Processing in Spatial Databases,' IEEE Transactions on Knowledge and Data Engineering, vol. 16(12), pp. 1555-1570, 2004   DOI   ScienceOn
9 D. Papadias, P. Kalnis, J Zhang, and Y. Tao, 'Efficient OLAP Operations in Spatial Data Warehouses,' Technical Report: HKUST-CS0l-01, University of Science & Technology, Hon Kong, 2001
10 ESRI, 'Spatial Data Warehousing for Hospital Organizations,' An ESRI White Paper, 1998. http://www.esri.com/library/whitepapers/pdfs/sdwho.pdf
11 W. H. Inmon, Building the Data Warehouse, 3rd Ed., John Wiley & Sons. Inc, 1996
12 V. Harinarayan, A. Rajaraman, and J. Ullman, 'Implementing Data Cubes Efficiently,' ACM SIGMOD, Vol.25, No.2, pp. 205-216, 1996   DOI   ScienceOn
13 J. Han, N. Stefanovic, and K. Koperski, 'Selective Materialization: An Efficient Method for Spatial Data Cube Construction,' In Research and Deve-lopment in Knowledge Discovery and Data Mining, pp. 144-158, 1998
14 F. Rao, L. Zhang, X. L. Yu, Y. Li, and Y. Chen, 'Spatial Hierarchy and OLAP-Favored Search in Spatial Data Warehouse,' DOLAP, pp. 48-55, 2003   DOI
15 J. Gray, A. Bosworth, A. Layman, and H. Pirahesh, 'Data Cube: a Relational Aggregation Operator Generalizing Group-by,' In Proc. 12th ICDE, pp. 152-159, 1996   DOI
16 L. Zhang, Y. Li, F. Rao, X. Yu, and Y. Chen, 'An approach to enabling spatial OLAP by aggregating on spatial hierarchy,' In Proc. Data Warehousing and Knowledge Discovery, pp. 35-44, 2003