Abstract
In this work, we study how to improve the efficiency and stability of querying reverse k-nearest-neighbor (RkNN) for moving objects. An approach named as ESA is presented in this paper. Different from the existing approaches, ESA selects k objects as pruning reference objects for each time of pruning. In this way, its greatly improves the query efficiency. ESA also reduces the communication cost and enhances the stability of the server by adaptively adjusting the objects’ safe regions. Experimental results verify the performance of our proposed approach.
This work is support by Municipal Nature Science Foundation of Shanghai under Grant No. 10ZR1421100, Innovation Program of Shanghai Education Commission under Grant No. 08YZ98, Postgraduate Construction of the Core Curriculum of University of Shanghai for Science and Technology under Grant No. 16000206 and Innovation Program of School of Optical-Electrical and Computer Engineering, USST, under Grant No. GDCX-T-102.
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Peng, D., Long, W., Huang, T., Huo, H. (2010). ESA: An Efficient and Stable Approach to Querying Reverse k-Nearest-Neighbor of Moving Objects. In: Wang, F.L., Gong, Z., Luo, X., Lei, J. (eds) Web Information Systems and Mining. WISM 2010. Lecture Notes in Computer Science, vol 6318. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16515-3_38
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DOI: https://doi.org/10.1007/978-3-642-16515-3_38
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