3-Dimensional wireless sensor network localization: A review

The proliferation of wireless sensor network (WSN) has shifted the focus to 3-Dimensional geometry rather than 2-Dimensional geometry. Since exact location of sensors has been the fundamental issue in wireless sensor network, node localization is essential for any wireless sensor network application...

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Main Authors: Najib, Y.N.A., Daud, H., Aziz, A.A., Razali, R.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.30618 /
Published: American Institute of Physics Inc. 2016
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006006298&doi=10.1063%2f1.4968168&partnerID=40&md5=f5cb98fcb9e72681f930e331257514da
http://eprints.utp.edu.my/30618/
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spelling utp-eprints.306182022-03-25T07:12:40Z 3-Dimensional wireless sensor network localization: A review Najib, Y.N.A. Daud, H. Aziz, A.A. Razali, R. The proliferation of wireless sensor network (WSN) has shifted the focus to 3-Dimensional geometry rather than 2-Dimensional geometry. Since exact location of sensors has been the fundamental issue in wireless sensor network, node localization is essential for any wireless sensor network applications. Most algorithms mainly focus on 2-Dimensional geometry, where the application of this algorithm will decrease the accuracy on 3-Dimensional geometry. The low rank attribute in WSN's node estimation makes the application of nuclear norm minimization as a viable solution for dimensionality reduction problems. This research proposes a novel localization algorithm for 3-Dimensional WSN which is nuclear norm minimization. The node localization is formulated via Euclidean Distance Matrix (EDM) and is then optimized using Nuclear-Norm Minimization (NNM). © 2016 Author(s). American Institute of Physics Inc. 2016 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006006298&doi=10.1063%2f1.4968168&partnerID=40&md5=f5cb98fcb9e72681f930e331257514da Najib, Y.N.A. and Daud, H. and Aziz, A.A. and Razali, R. (2016) 3-Dimensional wireless sensor network localization: A review. In: UNSPECIFIED. http://eprints.utp.edu.my/30618/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The proliferation of wireless sensor network (WSN) has shifted the focus to 3-Dimensional geometry rather than 2-Dimensional geometry. Since exact location of sensors has been the fundamental issue in wireless sensor network, node localization is essential for any wireless sensor network applications. Most algorithms mainly focus on 2-Dimensional geometry, where the application of this algorithm will decrease the accuracy on 3-Dimensional geometry. The low rank attribute in WSN's node estimation makes the application of nuclear norm minimization as a viable solution for dimensionality reduction problems. This research proposes a novel localization algorithm for 3-Dimensional WSN which is nuclear norm minimization. The node localization is formulated via Euclidean Distance Matrix (EDM) and is then optimized using Nuclear-Norm Minimization (NNM). © 2016 Author(s).
format Conference or Workshop Item
author Najib, Y.N.A.
Daud, H.
Aziz, A.A.
Razali, R.
spellingShingle Najib, Y.N.A.
Daud, H.
Aziz, A.A.
Razali, R.
3-Dimensional wireless sensor network localization: A review
author_sort Najib, Y.N.A.
title 3-Dimensional wireless sensor network localization: A review
title_short 3-Dimensional wireless sensor network localization: A review
title_full 3-Dimensional wireless sensor network localization: A review
title_fullStr 3-Dimensional wireless sensor network localization: A review
title_full_unstemmed 3-Dimensional wireless sensor network localization: A review
title_sort 3-dimensional wireless sensor network localization: a review
publisher American Institute of Physics Inc.
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006006298&doi=10.1063%2f1.4968168&partnerID=40&md5=f5cb98fcb9e72681f930e331257514da
http://eprints.utp.edu.my/30618/
_version_ 1741197437907763200
score 11.62408

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