Please use this identifier to cite or link to this item: https://doi.org/10.1109/SSDBM.2007.37
Title: iSEE: Efficient continuous k-nearest-neighbor monitoring over moving objects
Authors: Wu, W.
Tan, K.-L. 
Issue Date: 2007
Source: Wu, W.,Tan, K.-L. (2007). iSEE: Efficient continuous k-nearest-neighbor monitoring over moving objects. Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM. ScholarBank@NUS Repository. https://doi.org/10.1109/SSDBM.2007.37
Abstract: In this paper, we propose iSEE, a set of algorithms for efficient processing of continuous k-nearest-neighbor (CKNN) queries over moving objects. iSEE utilizes a grid index and incrementally updates the queries' results based on moving objects' explicit location update messages. We have three innovations in iSEE: a Visit Order Builder (VOB) method that dynamically constructs a query's optimal visit order to the cells in the grid index with low cost, an Efficient Expand (EFEX) algorithm which avoids unnecessary and redundant searching when updating a query's result, and an efficient algorithm that quickly identifies the cells that should be updated after a query's result is changed. Experimental results show that iSEE achieves a 2X speedup, when compared with the state-of-the-art CPM scheme. © 2007 IEEE.
Source Title: Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
URI: http://scholarbank.nus.edu.sg/handle/10635/42115
ISBN: 0769528686
ISSN: 10993371
DOI: 10.1109/SSDBM.2007.37
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