The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Aujourd'hui, la localisation des nœuds dans les réseaux de capteurs sans fil (WSN) constitue un problème complexe. En particulier, il est presque impossible de garantir qu’un algorithme donnant des résultats optimaux pour une topologie donnera des résultats optimaux pour toute autre topologie aléatoire. Dans cette étude, nous proposons un algorithme hybride centralisé, basé sur la plage et l'ancrage, appelé RH+, qui vise à combiner les puissantes fonctionnalités de deux techniques orthogonales : la mise à l'échelle multidimensionnelle classique (CMDS) et l'optimisation des ressorts de particules (PSO). En conséquence, nous constatons que notre approche hybride donne une solution à convergence rapide, résiliente aux erreurs de portée et très robuste aux changements de topologie. Dans toutes les topologies que nous avons étudiées, l'erreur d'estimation moyenne est inférieure à 0.5 m. lorsque la densité moyenne de nœuds est de 10 et que seulement 2.5 % des nœuds sont des balises.
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Can BASARAN, Sebnem BAYDERE, Gurhan KUCUK, "RH+: A Hybrid Localization Algorithm for Wireless Sensor Networks" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 6, pp. 1852-1861, June 2008, doi: 10.1093/ietcom/e91-b.6.1852.
Abstract: Today, localization of nodes in Wireless Sensor Networks (WSNs) is a challenging problem. Especially, it is almost impossible to guarantee that one algorithm giving optimal results for one topology will give optimal results for any other random topology. In this study, we propose a centralized, range- and anchor-based, hybrid algorithm called RH+ that aims to combine the powerful features of two orthogonal techniques: Classical Multi-Dimensional Scaling (CMDS) and Particle Spring Optimization (PSO). As a result, we find that our hybrid approach gives a fast-converging solution which is resilient to range-errors and very robust to topology changes. Across all topologies we studied, the average estimation error is less than 0.5 m. when the average node density is 10 and only 2.5% of the nodes are beacons.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.6.1852/_p
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@ARTICLE{e91-b_6_1852,
author={Can BASARAN, Sebnem BAYDERE, Gurhan KUCUK, },
journal={IEICE TRANSACTIONS on Communications},
title={RH+: A Hybrid Localization Algorithm for Wireless Sensor Networks},
year={2008},
volume={E91-B},
number={6},
pages={1852-1861},
abstract={Today, localization of nodes in Wireless Sensor Networks (WSNs) is a challenging problem. Especially, it is almost impossible to guarantee that one algorithm giving optimal results for one topology will give optimal results for any other random topology. In this study, we propose a centralized, range- and anchor-based, hybrid algorithm called RH+ that aims to combine the powerful features of two orthogonal techniques: Classical Multi-Dimensional Scaling (CMDS) and Particle Spring Optimization (PSO). As a result, we find that our hybrid approach gives a fast-converging solution which is resilient to range-errors and very robust to topology changes. Across all topologies we studied, the average estimation error is less than 0.5 m. when the average node density is 10 and only 2.5% of the nodes are beacons.},
keywords={},
doi={10.1093/ietcom/e91-b.6.1852},
ISSN={1745-1345},
month={June},}
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TY - JOUR
TI - RH+: A Hybrid Localization Algorithm for Wireless Sensor Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 1852
EP - 1861
AU - Can BASARAN
AU - Sebnem BAYDERE
AU - Gurhan KUCUK
PY - 2008
DO - 10.1093/ietcom/e91-b.6.1852
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2008
AB - Today, localization of nodes in Wireless Sensor Networks (WSNs) is a challenging problem. Especially, it is almost impossible to guarantee that one algorithm giving optimal results for one topology will give optimal results for any other random topology. In this study, we propose a centralized, range- and anchor-based, hybrid algorithm called RH+ that aims to combine the powerful features of two orthogonal techniques: Classical Multi-Dimensional Scaling (CMDS) and Particle Spring Optimization (PSO). As a result, we find that our hybrid approach gives a fast-converging solution which is resilient to range-errors and very robust to topology changes. Across all topologies we studied, the average estimation error is less than 0.5 m. when the average node density is 10 and only 2.5% of the nodes are beacons.
ER -