Many applications of wireless sensor networks (WSN) require information about the geographical location of each sensor node. Self-organization and localization capabilities are one of the most important requirements in sensor networks. This paper provides an overview of centralized distance-based algorithms for estimating the positions of nodes in a sensor network. We discuss and compare three approaches: semidefinite programming, simulated annealing and two-phase stochastic optimization-a hybrid scheme that we have proposed. We analyze the properties of all listed methods and report the results of numerical tests. Particular attention is paid to our technique-the two-phase method-that uses a combination of trilateration, and stochastic optimization for performing sensor localization. We describe its performance in the case of centralized and distributed implementations.
@article{bwmeta1.element.bwnjournal-article-amcv19i2p291bwm,
author = {Ewa Niewiadomska-Szynkiewicz and Micha\l\ Marks},
title = {Optimization schemes for wireless sensor network localization},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {19},
year = {2009},
pages = {291-302},
zbl = {1167.93305},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv19i2p291bwm}
}
Ewa Niewiadomska-Szynkiewicz; Michał Marks. Optimization schemes for wireless sensor network localization. International Journal of Applied Mathematics and Computer Science, Tome 19 (2009) pp. 291-302. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv19i2p291bwm/
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