Evolutionary and noise-aware data gathering for wireless sensor networks

This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing...

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Main Authors: Zhu B., Suzuki J., Boonma P.
Format: Book Series
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84869596835&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42773
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Institution: Chiang Mai University
id th-cmuir.6653943832-42773
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spelling th-cmuir.6653943832-427732017-09-28T06:38:52Z Evolutionary and noise-aware data gathering for wireless sensor networks Zhu B. Suzuki J. Boonma P. This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering. 2017-09-28T06:38:51Z 2017-09-28T06:38:51Z 2012-09-06 Book Series 18678211 2-s2.0-84869596835 10.1007/978-3-642-32615-8_5 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84869596835&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42773
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.
format Book Series
author Zhu B.
Suzuki J.
Boonma P.
spellingShingle Zhu B.
Suzuki J.
Boonma P.
Evolutionary and noise-aware data gathering for wireless sensor networks
author_facet Zhu B.
Suzuki J.
Boonma P.
author_sort Zhu B.
title Evolutionary and noise-aware data gathering for wireless sensor networks
title_short Evolutionary and noise-aware data gathering for wireless sensor networks
title_full Evolutionary and noise-aware data gathering for wireless sensor networks
title_fullStr Evolutionary and noise-aware data gathering for wireless sensor networks
title_full_unstemmed Evolutionary and noise-aware data gathering for wireless sensor networks
title_sort evolutionary and noise-aware data gathering for wireless sensor networks
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84869596835&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42773
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