Wireless sensor networks localization methods: Multidimensional scaling vs. semidefinite programming approach
Date Issued
2009-09-28
Author(s)
Davcev, Danco
Abstract
With the recent development of technology, wireless sensor networks
are becoming an important part of many applications such as health and
medical applications, military applications, agriculture monitoring, home and
office applications, environmental monitoring, etc. Knowing the location of a
sensor is important, but GPS receivers and sophisticated sensors are too
expensive and require processing power. Therefore, the localization wireless
sensor network problem is a growing field of interest. The aim of this paper is
to give a comparison of wireless sensor network localization methods, and
therefore, multidimensional scaling and semidefinite programming are chosen
for this research. Multidimensional scaling is a simple mathematical technique
widely-discussed that solves the wireless sensor networks localization problem.
In contrast, semidefinite programming is a relatively new field of optimization
with a growing use, although being more complex. In this paper, using
extensive simulations, a detailed overview of these two approaches is given,
regarding different network topologies, various network parameters and
performance issues. The performances of both techniques are highly
satisfactory and estimation errors are minimal.
are becoming an important part of many applications such as health and
medical applications, military applications, agriculture monitoring, home and
office applications, environmental monitoring, etc. Knowing the location of a
sensor is important, but GPS receivers and sophisticated sensors are too
expensive and require processing power. Therefore, the localization wireless
sensor network problem is a growing field of interest. The aim of this paper is
to give a comparison of wireless sensor network localization methods, and
therefore, multidimensional scaling and semidefinite programming are chosen
for this research. Multidimensional scaling is a simple mathematical technique
widely-discussed that solves the wireless sensor networks localization problem.
In contrast, semidefinite programming is a relatively new field of optimization
with a growing use, although being more complex. In this paper, using
extensive simulations, a detailed overview of these two approaches is given,
regarding different network topologies, various network parameters and
performance issues. The performances of both techniques are highly
satisfactory and estimation errors are minimal.
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