PML - tree Parallel Spatial Index Structure for Large Spatial Databases


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 7, No. 11, pp. 3323-3332, Nov. 2000
10.3745/KIPSTE.2000.7.11.3323,   PDF Download:

Abstract

In this paper, a new dynamic parallel index structure called a parallel multiple-layer(PML) tree is proposed. The PML-tree increases speed of query processing by distributing data objects evenly among the multiple data spaces using object distribution heuristics. The author proposes and implements two heuristic methods, absolute crowd index and relative crowd index for an even distribution of objects over the multiple disks on which the PML-tree resides. The PML-tree does not require extra search paths as in R-tree, and does not contain any duplicated entries in leaf node as in R -tree. The performance the PML-tree and the MXR-tree are compared and analyzed using test data. Compared with the MXR-tree, the PML-tree increases space utilization and improves query performances on a system with multiple disks and expected as an efficient index structure for spatial databases.


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Cite this article
[IEEE Style]
K. S. Bang, "PML - tree Parallel Spatial Index Structure for Large Spatial Databases," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 7, no. 11, pp. 3323-3332, 2000. DOI: 10.3745/KIPSTE.2000.7.11.3323.

[ACM Style]
Kap San Bang. 2000. PML - tree Parallel Spatial Index Structure for Large Spatial Databases. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 7, 11, (2000), 3323-3332. DOI: 10.3745/KIPSTE.2000.7.11.3323.