Affiliation:
1. Harbin Engineering University
Abstract
The performance of the spatial range query algorithms based on Brute-Force method, R-tree, VA-file and NB-tree suffers greatly in high-dimensional space. So the reduction of the dimensionality is the key to the spatial range query in high-dimensional space. The paper uses the parallel technique to present a spatial range query parallel algorithm in high-dimensional space. The algorithm transforms d-dimensional spatial range query to the linear space on d slave node processors. The d slave node processors run parallel. The master node processor only need calculate the union of d results which d slave node processors return. The experimental results indicate that its performance is better than that of the spatial range query algorithms based on Brute-Force method, R-tree, VA-file, NB-tree.
Publisher
Trans Tech Publications, Ltd.
Reference6 articles.
1. Zhongxiao Hao: Spatio Temporal Database Query and Reasoning (Science Press, Beijing 2010).
2. Beyer K, Goldstein J, Ramakrishnan R: When is nearest neighbor, meaningful, edited by the 7th International Conference on Database Theory (1999), p.217.
3. Weber R, Blott S: An Approximation-based data structure for similarity search. ESPRIT Project HERMES NO. 9141 (1997).
4. Manuel J F, Joaquim A J: Indexing high-dimensional data for content-based retrieval in large databases, edited by the 8th International Conference on Database Systems for Advanced Applications (2003), p.267.
5. CHEN Guo-Liang, SUN Guang-Zhong, XU Yun, LU Min: Methodology of Research on Parallel Algorithms, submitted to Chinese Journal of Computers, Vol. 31(9) (2008), p.1493.