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Reseach Article

A Distributed Method for Localization in Large-Scale Sensor Networks based on Jarvis

by Yassine Sabri, Najib El Kamoun
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 165 - Number 3
Year of Publication: 2017
Authors: Yassine Sabri, Najib El Kamoun
10.5120/ijca2017913826

Yassine Sabri, Najib El Kamoun . A Distributed Method for Localization in Large-Scale Sensor Networks based on Jarvis. International Journal of Computer Applications. 165, 3 ( May 2017), 1-9. DOI=10.5120/ijca2017913826

@article{ 10.5120/ijca2017913826,
author = { Yassine Sabri, Najib El Kamoun },
title = { A Distributed Method for Localization in Large-Scale Sensor Networks based on Jarvis },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 165 },
number = { 3 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume165/number3/27550-2017913826/ },
doi = { 10.5120/ijca2017913826 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:11:22.121076+05:30
%A Yassine Sabri
%A Najib El Kamoun
%T A Distributed Method for Localization in Large-Scale Sensor Networks based on Jarvis
%J International Journal of Computer Applications
%@ 0975-8887
%V 165
%N 3
%P 1-9
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper addresses target localization problem in a cooperative 3- D wireless sensor network (WSN).We employ a hybrid system that fuses distance and angle measurements, extracted from the received signal strength (RSS) and angle-of-arrival (AoA) information, respectively. Based on range measurement model and simple geometry, we derive a novel convex estimator based on Jarv’s scan . The network is said to be uniquely localizable if there is a unique set of locations consistent with the given data.This paper presents an improved localization algorithm with high accuracy in large-scale Sensor networks with a large number of sensor nodes based on the Jarvis’ March ,called SLSNJ. the Jarvis’ March adapted here for our approximation technique to determining the convex hull of a set of sensors used instead of the Grid-Scan method,to take into account the requirements in memory, to make it scalable and rapidly convergent with small location estimation error.We verify our algorithm in various scenarios and compare it with AT-Dist method. Our simulation results show that the new estimators have excellent performance in terms of the estimation accuracy and convergence, and they confirm the effectiveness of combining two radio measurements in large-scale.

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Index Terms

Computer Science
Information Sciences

Keywords

Wireless Sensor Network (WSN) Routing Multiple Sink Localization Geographic Routing