An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue

Rani, S; Babbar, H; Kaur, P; Alshehri, MD; Shah, SHA

An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue

Rani, S Babbar, H Kaur, P Alshehri, MD Shah, SHA

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Intelligent Transportation Systems, 2023, 24, (2), pp. 2548-2555
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Rani, S
dc.contributor.author	Babbar, H
dc.contributor.author	Kaur, P
dc.contributor.author	Alshehri, MD
dc.contributor.author	Shah, SHA
dc.date.accessioned	2023-03-20T02:19:44Z
dc.date.available	2023-03-20T02:19:44Z
dc.date.issued	2023-02-01
dc.identifier.citation	IEEE Transactions on Intelligent Transportation Systems, 2023, 24, (2), pp. 2548-2555
dc.identifier.issn	1524-9050
dc.identifier.issn	1558-0016
dc.identifier.uri	http://hdl.handle.net/10453/167697
dc.description.abstract	Maritime search and rescue plays an important part in ensuring the safety of life at sea. When using wireless Sensor Network (WSN) technologies in maritime, nevertheless, it endures from situations where the measurement information is inadequate. In computing and networking for maritime applications, Wireless Sensor Network (WSNs) is a rising inflexion because of its amazing features. Simultaneously, there are some challenges faced by WSNs and node localization is one of them. Node localization is an important factor because until the location of reporting node is unknown, the data sensed by that node is totally useless. The main aim of this paper is towards gaining more improvement in localization by using swarm intelligence algorithm. To achieve this aim, a range-free and distributed method by using the application of salp swarm algorithm for moving target node in network for maritime rescue is proposed. The results are compared with existing algorithm Particle Swarm Optimization (PSO) and Butterfly Optimization Algorithm (BOA). The proposed method has approximately 10% less localization error as compared to PSO and BOA. The proposed algorithm is validated in terms of localization accuracy, localized nodes, localization errors and computing time.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Intelligent Transportation Systems
dc.relation.isbasedon	10.1109/TITS.2021.3129914
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0905 Civil Engineering, 1507 Transportation and Freight Services
dc.subject.classification	Logistics & Transportation
dc.title	An Optimized Approach of Dynamic Target Nodes in Wireless Sensor Network Using Bio Inspired Algorithms for Maritime Rescue
dc.type	Journal Article
utslib.citation.volume	24
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0905 Civil Engineering
utslib.for	1507 Transportation and Freight Services
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-20T02:19:43Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	24
utslib.citation.issue	2

Abstract:

Maritime search and rescue plays an important part in ensuring the safety of life at sea. When using wireless Sensor Network (WSN) technologies in maritime, nevertheless, it endures from situations where the measurement information is inadequate. In computing and networking for maritime applications, Wireless Sensor Network (WSNs) is a rising inflexion because of its amazing features. Simultaneously, there are some challenges faced by WSNs and node localization is one of them. Node localization is an important factor because until the location of reporting node is unknown, the data sensed by that node is totally useless. The main aim of this paper is towards gaining more improvement in localization by using swarm intelligence algorithm. To achieve this aim, a range-free and distributed method by using the application of salp swarm algorithm for moving target node in network for maritime rescue is proposed. The results are compared with existing algorithm Particle Swarm Optimization (PSO) and Butterfly Optimization Algorithm (BOA). The proposed method has approximately 10% less localization error as compared to PSO and BOA. The proposed algorithm is validated in terms of localization accuracy, localized nodes, localization errors and computing time.

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http://hdl.handle.net/10453/167697