A threshold-based algorithm for continuous monitoring of k nearest neighbors

被引:60
作者
Mouratidis, K
Papadias, D
Bakiras, S
Tao, YF
机构
[1] Hong Kong Univ Sci & Technol, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
关键词
spatial databases; location-dependent and sensitive; query processing;
D O I
10.1109/TKDE.2005.172
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naive solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations.
引用
收藏
页码:1451 / 1464
页数:14
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