SpaseLoc: An adaptive subproblem algorithm for scalable wireless sensor network localization

被引：41
作者：
Carter, Michael W. [1 ]
Jin, Holly H.
Saunders, Michael A.
Ye, Yinyu
机构：
[1] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON M5S 3G8, Canada
[2] Stanford Univ, Dept Management Sci & Engn, Stanford, CA 94305 USA
来源：
SIAM JOURNAL ON OPTIMIZATION | 2006年 / 17卷 / 04期
关键词：
sensor localization; semidefinite programming; large-scale optimization;
D O I：
10.1137/040621600
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
An adaptive rule-based algorithm, SpaseLoc, is described to solve localization problems for ad hoc wireless sensor networks. A large problem is solved as a sequence of very small subproblems, each of which is solved by semidefinite programming relaxation of a geometric optimization model. The subproblems are generated according to a set of sensor/anchor selection rules. Computational results compared with existing approaches show that the SpaseLoc algorithm scales well and provides excellent localization accuracy.
引用
收藏
页码：1102 / 1128
页数：27
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