Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm

This paper explores the possibility of enhancing consensus achievement of decentralized sensors by establishing cooperative behavior between sensor agents. To these ends, a novel particle swarm optimization framework to achieve robust consensus of decentralized sensors is devised to distribute sensi...

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Main Authors: Hyunseok Kim, Seongju Chang, Jinsul Kim
Format: Article
Language:English
Published: Wiley 2014-04-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/950683
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author Hyunseok Kim
Seongju Chang
Jinsul Kim
author_facet Hyunseok Kim
Seongju Chang
Jinsul Kim
author_sort Hyunseok Kim
collection DOAJ
description This paper explores the possibility of enhancing consensus achievement of decentralized sensors by establishing cooperative behavior between sensor agents. To these ends, a novel particle swarm optimization framework to achieve robust consensus of decentralized sensors is devised to distribute sensing information via local fusing with neighbors rather than through centralized control; the new framework showed a 16.5 percent improvement in consensus achievement as compared to the classic majority rule method. Noteworthy enhancements in consensus achievement are also pertinent to the comparable situation of decentralized sensor systems.
format Article
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institution Kabale University
issn 1550-1477
language English
publishDate 2014-04-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-afb4fabba99b4648a731442e03e7f92f2025-02-03T06:45:25ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-04-011010.1155/2014/950683950683Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization AlgorithmHyunseok Kim0Seongju Chang1Jinsul Kim2 IT Convergence Technology Research Laboratory, Electronics and Telecommunications Research Institute, Daejeon 305-700, Republic of Korea Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Republic of Korea School of Electronics and Computer Engineering, Chonnam National University, Gwangju 500-757, Republic of KoreaThis paper explores the possibility of enhancing consensus achievement of decentralized sensors by establishing cooperative behavior between sensor agents. To these ends, a novel particle swarm optimization framework to achieve robust consensus of decentralized sensors is devised to distribute sensing information via local fusing with neighbors rather than through centralized control; the new framework showed a 16.5 percent improvement in consensus achievement as compared to the classic majority rule method. Noteworthy enhancements in consensus achievement are also pertinent to the comparable situation of decentralized sensor systems.https://doi.org/10.1155/2014/950683
spellingShingle Hyunseok Kim
Seongju Chang
Jinsul Kim
Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
International Journal of Distributed Sensor Networks
title Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
title_full Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
title_fullStr Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
title_full_unstemmed Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
title_short Consensus Achievement of Decentralized Sensors Using Adapted Particle Swarm Optimization Algorithm
title_sort consensus achievement of decentralized sensors using adapted particle swarm optimization algorithm
url https://doi.org/10.1155/2014/950683
work_keys_str_mv AT hyunseokkim consensusachievementofdecentralizedsensorsusingadaptedparticleswarmoptimizationalgorithm
AT seongjuchang consensusachievementofdecentralizedsensorsusingadaptedparticleswarmoptimizationalgorithm
AT jinsulkim consensusachievementofdecentralizedsensorsusingadaptedparticleswarmoptimizationalgorithm