D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling
This paper proposes a distributed localization algorithm which can be applied to an irregular three-dimensional wireless sensor network, considering the algorithm accuracy and complexity. The algorithm uses clusters to eliminate the multihop distance errors. An anchor node position optimization sche...
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2015/103564 |
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doaj-f2080b2e5c954961a788216e7944e75b2020-11-25T02:59:01ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-02-011110.1155/2015/103564103564D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional ScalingJin FanBaohui ZhangGuojun DaiThis paper proposes a distributed localization algorithm which can be applied to an irregular three-dimensional wireless sensor network, considering the algorithm accuracy and complexity. The algorithm uses clusters to eliminate the multihop distance errors. An anchor node position optimization scheme is proposed to maximize the uniformity of each subnetwork. The proposed algorithm also employs a new three-dimensional coordinate transformation algorithm, which helps to reduce the errors introduced by coordinate integration between clusters and improves the localization precision. The simulation and performance analysis results show that the localization accuracy of the D3D-MDS algorithm increases by 49.1% compared with 3D-DV-HOP and 38.6% compared with 3D-MDS-MAP. This distributed localization scheme also demonstrates a low computational complexity compared with other centralized localization algorithms.https://doi.org/10.1155/2015/103564 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jin Fan Baohui Zhang Guojun Dai |
spellingShingle |
Jin Fan Baohui Zhang Guojun Dai D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling International Journal of Distributed Sensor Networks |
author_facet |
Jin Fan Baohui Zhang Guojun Dai |
author_sort |
Jin Fan |
title |
D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling |
title_short |
D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling |
title_full |
D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling |
title_fullStr |
D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling |
title_full_unstemmed |
D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling |
title_sort |
d3d-mds: a distributed 3d localization scheme for an irregular wireless sensor network using multidimensional scaling |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2015-02-01 |
description |
This paper proposes a distributed localization algorithm which can be applied to an irregular three-dimensional wireless sensor network, considering the algorithm accuracy and complexity. The algorithm uses clusters to eliminate the multihop distance errors. An anchor node position optimization scheme is proposed to maximize the uniformity of each subnetwork. The proposed algorithm also employs a new three-dimensional coordinate transformation algorithm, which helps to reduce the errors introduced by coordinate integration between clusters and improves the localization precision. The simulation and performance analysis results show that the localization accuracy of the D3D-MDS algorithm increases by 49.1% compared with 3D-DV-HOP and 38.6% compared with 3D-MDS-MAP. This distributed localization scheme also demonstrates a low computational complexity compared with other centralized localization algorithms. |
url |
https://doi.org/10.1155/2015/103564 |
work_keys_str_mv |
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1724704120234835968 |