Residual energy-based cluster-head selection in WSNs for IoT application

Behera, TM; Mohapatra, SK; Samal, UC; Khan, MS; Daneshmand, M; Gandomi, AH

Residual energy-based cluster-head selection in WSNs for IoT application

Behera, TM Mohapatra, SK Samal, UC Khan, MS Daneshmand, M Gandomi, AH

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2019, 6, (3), pp. 5132-5139
Issue Date:: 2019-06-01

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Field	Value	Language
dc.contributor.author	Behera, TM
dc.contributor.author	Mohapatra, SK
dc.contributor.author	Samal, UC
dc.contributor.author	Khan, MS
dc.contributor.author	Daneshmand, M
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2020-05-14T04:47:50Z
dc.date.available	2020-05-14T04:47:50Z
dc.date.issued	2019-06-01
dc.identifier.citation	IEEE Internet of Things Journal, 2019, 6, (3), pp. 5132-5139
dc.identifier.issn	2327-4662
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/140711
dc.description.abstract	© 2014 IEEE. Wireless sensor networks (WSNs) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head (CH) can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. This paper focuses on an efficient CH election scheme that rotates the CH position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy, and an optimum value of CHs to elect the next group of CHs for the network that suits for IoT applications, such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the low energy adaptive clustering hierarchy protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Internet of Things Journal
dc.relation.isbasedon	10.1109/JIOT.2019.2897119
dc.rights	© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.title	Residual energy-based cluster-head selection in WSNs for IoT application
dc.type	Journal Article
utslib.citation.volume	6
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-05-14T04:47:43Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	6
utslib.start-page	5132
utslib.citation.issue	3

Abstract:

© 2014 IEEE. Wireless sensor networks (WSNs) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head (CH) can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. This paper focuses on an efficient CH election scheme that rotates the CH position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy, and an optimum value of CHs to elect the next group of CHs for the network that suits for IoT applications, such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the low energy adaptive clustering hierarchy protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.

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http://hdl.handle.net/10453/140711