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...
Main Authors: | , |
---|---|
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 |
id |
doaj-4004617f60324d8f93f9fe69d548e9a0 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT serapkaragol twodimensionalsensorlocalizationusingmn2algorithmindifferenttypesofdistributedfields AT doganyildiz twodimensionalsensorlocalizationusingmn2algorithmindifferenttypesofdistributedfields |
_version_ |
1725743640615059456 |