Indexing multidimensional data is inherently complex leading to slow query processing. This behavior becomes more pronounced with the increase in database size and/or number of dimensions. In this paper, we address this issue by processing an index structure in parallel. First, we study different ways of partitioning an index structure. We then propose efficient algorithms for processing each query in parallel on the index structure. Using these strategies, we parallelized two multidimensional index structures - R* and LIB and evaluated the performance gains for the Gazetteer and the Catalog data of the Alexandria Digital Library on the Meiko CS-2.
|Number of pages||8|
|Journal||IEEE Symposium on Parallel and Distributed Processing - Proceedings|
|Publication status||Published - 1 Dec 1996|
|Event||Proceedings of the 1996 8th IEEE Symposium on Parallel and Distributed Processing - New Orleans, LA, USA|
Duration: 23 Oct 1996 → 26 Oct 1996
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