W. Choi and S. Lee (Korea)
Spatio-temporal data warehouses, Spatio-temporal OLAP, aggregation queries, adaptive cell-based index, ST -Cube
Recently, there have been various research efforts to de velop strategies for accelerating OLAP operations on im mense amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a sin gle R-tree variant for spatial dimension and numerous B trees for temporal dimension. The multi-tree based frame works, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called ST -Cube(Spatio-Temporal Cube). The ST -Cube is an adaptive cell based index structure to handle aggrega tion queries over spatio-temporal data. Through the exten sive performance studies, we observed that the ST -Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree based frameworks.
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