Abstract
In this paper, we propose a parallel multidimensional index structure and range search and k-NN search methods for the index structures. The proposed index structure is nP(processor)-n×mD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure increases fan-out and reduces the height of an index tree. Also, the proposed range search methods are designed to maximize I/O parallelism of the index structure. Finally, we present a new method to transform k-NN queries to range search queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.
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Bok, K.S., Song, S.I., Yoo, J.S. (2006). Efficient k-Nearest Neighbor Searches for Parallel Multidimensional Index Structures. In: Li Lee, M., Tan, KL., Wuwongse, V. (eds) Database Systems for Advanced Applications. DASFAA 2006. Lecture Notes in Computer Science, vol 3882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11733836_64
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DOI: https://doi.org/10.1007/11733836_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33337-1
Online ISBN: 978-3-540-33338-8
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