Abstract
An efficient index structure for complex multi-dimensional objects is one of the most challenging requirements in non-traditional applications such as geographic information systems, computer-aided design, and multimedia databases. In this paper we first propose a main memory data structure for complex multi-dimensional objects. Then, we present an extension of the existing multi-dimensional index structure. Among existing multi-dimensional index structures, the popular R*-tree is selected. The R*-tree is coupled with the main memory data structure to improve the performance of spatial query processing. An analytical model is developed for our index structure. Experimental results show that the analytical model is accurate, the relative error being below 15%. The performance of our index structure is compared with that of a state-of-the-art index structure by experimental measurements. Our index structure outperforms the state-of-the-art index structure due to its ability to reduce a large amount of storage.
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References
A. Henrich, H.W. Six, and P. Widmayer. “The LSD Tree: Spatial access to multi-dimensional point and non-point objects,” Proceedings of the 15th International Conference on Very Large Data Bases, 45-53, 1989.
N. Beckmann, H.P. Kriegel, R. Schneider, and B. Seeger. “The R*-tree: An efficient and robust access method for points and rectangles,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 322-331, 1990.
S. Berchtold, D.A. Keim, and H.P. Kriegel. “The X-tree: An index structure for high-dimensional data,” Proceedings of the 22nd International Conference on Very Large Data Bases, 45-53, 1996.
H. Samet. The design and analysis of spatial data structures. Addison-Wesley, 1990.
J.A. Orenstein. “Spatial query processing in an object-oriented database system,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 326-336, 1986.
R. Schneider and H.P. Kriegel. “The TR*-tree: A new representation of polygonal objects supporting spatial queries and operations,” Proceedings of the 7th Workshop on Computational Geometry. Lecture Notes in Computer Science 553, Springer-Verlag, 249-264, 1991.
J.A. Orenstein. “Redundancy in spatial databases,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 294-305, 1989.
Y.J. Lee, D.M. Lee, S.J. Ryu, and C.W. Chung. “Controlled decomposition strategy for complex spatial objects,” Proceedings of the 7th International Conference on Database and Expert Systems Applications (DEXA), Lecture Notes in Computer Science 1134, Springer-Verlag: Zurich Switzerland, 207-223, 1996.
T. Brinkhoff, H.P. Kriegel, R. Schneider, and B. Seeger. “GeneSys: A system for efficient spatial query processing,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 519-519, 1994.
T. Brinkhoff, H.P. Kriegel, R. Schneider, and B. Seeger. “Multi-step processing of spatial joins,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 197-208, 1994.
A. Guttman. “R-Trees: A dynamic index structure for spatial searching,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 47-57, 1984.
F.P. Preparata and M.I. Shamos. Computational Geometry: An Introduction. Springer-Verlag: Germany, 36-88, 1985.
J. Nievergelt and H. Hinterberger. “The grid file: An adaptable, symmetric multikey file structure,” ACM Transactions on Database Systems, Vol. 9(1):38-71, 1984.
H. Samet. “The quadtree and related hierarchical data structures,” ACM Computing Surveys, Vol. 16(2):187-260, 1984.
A. Hutflesz, H.W. Six, and P. Widmayer. “The R-file: An efficient access structure for proximity queries,” Proc. of 6th Int. Conf. on Data Engineering, 372-379, 1990.
M.J. Carey, D.J. Dewitt, M.J. Franklin, N.E. Hall, M. McAuliffe, J.F. Naughton, D.T. Schuh, M.H. Solomon, C.K. Tan, O. Tsatalos, S. White and M.J. Zwilling. “Shoring up persistent applications,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 383-394, 1994.
T. Brinkhoff, H.P. Kriegel, and B. Seeger. “Efficient processing of spatial joins using R-trees,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 237-246, 1993.
Y. Theodoridis and T. Sellis. “A model for the prediction of R-tree performance,” Proceedings of the 15th ACM Symposium on Principles of Database Systems (PODS), 161-171, 1996.
C. Faloutsos, T. Sellis, and N. Roussopoulos. “Analysis of object oriented spatial access methods,” Proceedings of the ACM SIGMOD International Conference on Management of Data, 426-439, May 1987.
I. Kamel and C. Faloutsos. “On packing R-trees,” Proceedings of the 2nd international conference of information and knowledge management (CIKM), 490-499, 1993.
Y.W. Huang, N. Jing, and E.A. Rundensteiner. “A cost model for estimating the performance of spatial joins using R-trees,” Proceedings of the 9th International Conference on Scientific and Statistical Database Management, 30-38, 1997.
Y. Theodoridis, E. Stefanakis, and T. Sellis. “Cost models for join queries in spatial databases,” Proceedings of the 14th International Conference on Data Engineering, 476-483, 1998.
D.E. Knuth. The art of Computer Programming. Vol. 3: Sorting and Searching, Addition-Wesley: Reading, MA, 1973.
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Lee, YJ., Chung, CW. The DR-tree: A Main Memory Data Structure for Complex Multi-dimensional Objects. GeoInformatica 5, 181–207 (2001). https://doi.org/10.1023/A:1011494316133
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DOI: https://doi.org/10.1023/A:1011494316133