SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
A cost model for nearest neighbor search in high-dimensional data space
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Horizontally divided signature files on a parallel machine architecture
Journal of Systems Architecture: the EUROMICRO Journal
Vertically-partitioned parallel signature file method
Journal of Systems Architecture: the EUROMICRO Journal - Heterogeneous distributed and parallel architectures: hardware, software and design tools
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A New High-Dimensional Index Structure Using a Cell-Based Filtering Technique
ADBIS-DASFAA '00 Proceedings of the East-European Conference on Advances in Databases and Information Systems Held Jointly with International Conference on Database Systems for Advanced Applications: Current Issues in Databases and Information Systems
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A large number of high-dimensional index structures suffer from the so called 'dimensional curse' problem, i.e., the retrieval performance becomes increasingly degraded as the dimensionality is increased. To solve this problem, the cell-based filtering (CBF) scheme has been proposed, but it shows a linear decrease in performance as the dimensionality is increased. In this paper, we develop a parallel CBF scheme under an SN(Shared Nothing) cluster-based parallel architecture, so as to cope with the linear decrease in retrieval performance. In addition, we devise data insertion, range query and k-NN query processing algorithms which are suitable for the SN parallel architecture. Finally, we show that our parallel CBF scheme achieves good retrieval performance in proportion to the number of servers in the SN architecture and it outperforms a parallel version of the VA-File when the dimensionality is over 10.