The Transactions of the Korea Information Processing Society (한국정보처리학회논문지)

Korea Information Processing Society (한국정보처리학회)
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PML-tree : Parallel Spatial Index Structure for Large Spatial Databases

PML-tree : 대용량 공간데이터베이스를 위한 병렬처리 공간색인구조

  • 방갑산 (한성대학교 정보시스템공학과)
  • Published : 2000.11.01
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Abstract

본 논문에서는 PML-트리라는 공간색인구조를 제안한다. PML-트리는 object distribution heuristics를 사용하여 공간 데이터 객체를 여러 개의 데이터 공간에 균일하게 배치함으로써 질의처리 속도를 향상시킨다. 두 가지의 object distribution heuristics(absolute crowd index와 relative crowd index)가 제안이 된다. PML-트리는 공간 객체를 분배함으로써 R+-트리의 말단 노드 내에 존재하는 데이터의 중복을 제거하면서, R-트리의 단점인 색인 사각형들 사이에 중첩을 허용치 않는다. PML-트리의 성능은 여러 타입의 테스트 데이터를 사용하여 MXR-트리와 비교된다. PML-트리는 MXR-트리에 비해 높은 공간활용도와 빠른 질의 반응시간을 보임으로써 공간 데이터베이스를 위한 효율적인 색인구조로 사용이 될 것으로 기대된다.

Keywords

References

  1. Banerjee, J. and Kim, W., Supporting VLSI geometry operation in a Database System, Proc. of the IEEE 2nd International Conf. on Data Engineering, pp.409-415, 1986
  2. Bang, K. S. and Lu, Huizhu, A Simulation on an Index Structure for the Spatial object, Proc. of the International Simulation Technology Conf. (SIMTEC'92), November, pp.178-183, 1992
  3. Bang, K. S. and Lu, Huizhu, An Application of the multi-R tree to the VLSI circuit layout design, Proc 9th International Conf on System Engineering, University of Nevada Las Vegas, pp.295-299, 1993
  4. Bang, K. S. and Lu, Huizhu, SMR-tree : an efficient Index Structure for Spatial Databases, Proc. of the 1995 ACM Symposium on applied Computing, Nashville, February, pp.46-50, 1995 https://doi.org/10.1145/315891.315902
  5. Bang, K. S. and Lu, Huizhu, An Efficient Index Structure for Spatial Databases, Journal of Database Management, Vol.7, No.3, Summer, pp.3-15, 1996
  6. Beckmann, N and Kriegel, H. P. The R*-tree An Efficient and Robust Access Method for Points and Rectangles, ACM SIGMOD, pp. 322-331, 1990 https://doi.org/10.1145/93605.98741
  7. Bureau of the Census, Tiger/Line File, 1992 Technical Documentation, Bureau of the Census. Washington, DC, 1993
  8. Gunther, O., The Design of the Cell tree An Object Oriented Indox Structure for Geometric Databases, IEEE 5th International Conference on Data Engineering, pp. 598-605. 1989
  9. Guttman, A., R-Trees : A Dynamic Index Structure for Spatial Searching, Proc. of the ACM SIGMOD, pp.47-57, 1984 https://doi.org/10.1145/602259.602266
  10. Kamel, I. and Faloutsos, C, Parallel R-tree, ACM SIGMOD pp.195-204, 1992
  11. Hoel, E. G. and Samet, H., A Qualitative Comparison tudy of Data Structures for Large Segment Databases, ACM SIGMOD, pp.205-214, 1992
  12. Lomet, D B, A review of Recent Work on Multiple attribute Access Methods, ACM SIGMOD Record, Vol.21, No.3, pp.56-63, 1992 https://doi.org/10.1145/140979.141006
  13. Oosterom, P. V. and Den, Bos, J. V., An Object-Oriented Approach to the Design of Geographic Information systems, Computers & Graphies, Vol. 13, No. 4, pp409-418, 1989
  14. Osawa, Y. and Sakauchi, M., A New Tree Type Data Structure with Homogeneous Node Suitable for a Very Large Spatial Databases, Proc. of the IEEE 6th International Conference on Data Engineering, pp.296-303, 1990 https://doi.org/10.1109/ICDE.1990.113481
  15. Sellis, T., Roussopoulos, T. and Faloutsos, C., R-tree A Dynamic Index for Multi-dimensional objects, Proc. of the 13th VLBD Conference, pp.507-518, 1987
  16. Soffer, A. and Samet, H., Pictorial query by image similarity, IEEE Proceedings of the 13th International conf. on Pattern Recognition, pp. 114-119, 1996