Continuous aggregate nearest neighbor queries

被引：31

作者：

Elmongui, Hicham G. ^{[1
]}

Mokbel, Mohamed F. ^{[2
]}

Aref, Walid G. ^{[3
]}

机构：

[1] Univ Alexandria, Fac Engn, Dept Comp & Syst Engn, Alexandria 21544, Egypt

[2] Univ Minnesota Twin Cities, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA

[3] Purdue Univ, Dept Comp Sci, W Lafayette, IN 47907 USA

来源：

GEOINFORMATICA | 2013年 / 17卷 / 01期

基金：

美国国家科学基金会;

关键词：

Continuous query; Spatio-temporal query; Aggregate nearest neighbor;

D O I：

10.1007/s10707-011-0149-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper addresses the problem of continuous aggregate nearest-neighbor (CANN) queries for moving objects in spatio-temporal data stream management systems. A CANN query specifies a set of landmarks, an integer k, and an aggregate distance function f (e.g., min, max, or sum), where f computes the aggregate distance between a moving object and each of the landmarks. The answer to this continuous query is the set of k moving objects that have the smallest aggregate distance f. A CANN query may also be viewed as a combined set of nearest neighbor queries. We introduce several algorithms to continuously and incrementally answer CANN queries. Extensive experimentation shows that the proposed operators outperform the state-of-the-art algorithms by up to a factor of 3 and incur low memory overhead.

引用

页码：63 / 95

页数：33