Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields

Wireless Sensor Network (WSN) refers to a group of locationally dispensed and dedicated sensors that observe and record physical and environmental conditions and coordinate the aggregated data at a centrical location. To serve new applications, localization is largely used in WSNs to define the curr...

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Main Authors: Serap Karagol, Dogan Yildiz
Format: Article
Language:English
Published: International Science and Engineering Society, o.s. 2017-05-01
Series:International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
Online Access:http://ijates.org/index.php/ijates/article/view/217
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spelling doaj-4004617f60324d8f93f9fe69d548e9a02020-11-24T22:29:40ZengInternational Science and Engineering Society, o.s.International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems1805-54432017-05-0162526010.11601/ijates.v6i2.217119Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed FieldsSerap Karagol0Dogan Yildiz1ONDOKUZ MAYIS UNIVERSITYONDOKUZ MAYIS UNIVERSITYWireless Sensor Network (WSN) refers to a group of locationally dispensed and dedicated sensors that observe and record physical and environmental conditions and coordinate the aggregated data at a centrical location. To serve new applications, localization is largely used in WSNs to define the current location of the sensor nodes. In this paper, first, the proposed mN/2 algorithms performance compared with GPS, 3N, 3/2N and 3/2N(2) algorithms. The mN/2 algorithm is especially effective in very sparse networks where other algorithms usually fail. Even when the algorithm cannot locate a given node, it produces a polygonal estimate of the region in which the node is located. Monte Carlo simulations show that this algorithm performs better than other algorithms. Secondly, Uniform, Beta, Weibull, Gamma and Generalized Pareto distributed networks were used for localization using the mN/2 algorithm. The localization performance of the networks are evaluated and compared using MATLAB simulations.http://ijates.org/index.php/ijates/article/view/217
collection DOAJ
language English
format Article
sources DOAJ
author Serap Karagol
Dogan Yildiz
spellingShingle Serap Karagol
Dogan Yildiz
Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
author_facet Serap Karagol
Dogan Yildiz
author_sort Serap Karagol
title Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
title_short Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
title_full Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
title_fullStr Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
title_full_unstemmed Two Dimensional Sensor Localization Using mN/2 Algorithm in Different Types of Distributed Fields
title_sort two dimensional sensor localization using mn/2 algorithm in different types of distributed fields
publisher International Science and Engineering Society, o.s.
series International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems
issn 1805-5443
publishDate 2017-05-01
description Wireless Sensor Network (WSN) refers to a group of locationally dispensed and dedicated sensors that observe and record physical and environmental conditions and coordinate the aggregated data at a centrical location. To serve new applications, localization is largely used in WSNs to define the current location of the sensor nodes. In this paper, first, the proposed mN/2 algorithms performance compared with GPS, 3N, 3/2N and 3/2N(2) algorithms. The mN/2 algorithm is especially effective in very sparse networks where other algorithms usually fail. Even when the algorithm cannot locate a given node, it produces a polygonal estimate of the region in which the node is located. Monte Carlo simulations show that this algorithm performs better than other algorithms. Secondly, Uniform, Beta, Weibull, Gamma and Generalized Pareto distributed networks were used for localization using the mN/2 algorithm. The localization performance of the networks are evaluated and compared using MATLAB simulations.
url http://ijates.org/index.php/ijates/article/view/217
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AT doganyildiz twodimensionalsensorlocalizationusingmn2algorithmindifferenttypesofdistributedfields
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