A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN

In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of repla...
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Autor*in:	Haewon Byeon [verfasserIn] Santosh Kumar [verfasserIn] Divya Mahajan [verfasserIn] K. Haribabu [verfasserIn] M. Sivaprakash [verfasserIn] Harshal Patil [verfasserIn] J. Sunil [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN

Übergeordnetes Werk:	In: Results in Control and Optimization - Elsevier, 2021, 14(2024), Seite 100379-
Übergeordnetes Werk:	volume:14 ; year:2024 ; pages:100379-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.rico.2024.100379

Katalog-ID:	DOAJ095677429

Internformat


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520			\|a In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.
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650		4	\|a Vortex search
650		4	\|a Improved dwarf mongoose optimization
650		4	\|a Underwater WSN
653		0	\|a Applied mathematics. Quantitative methods
700	0		\|a Santosh Kumar \|e verfasserin \|4 aut
700	0		\|a Divya Mahajan \|e verfasserin \|4 aut
700	0		\|a K. Haribabu \|e verfasserin \|4 aut
700	0		\|a M. Sivaprakash \|e verfasserin \|4 aut
700	0		\|a Harshal Patil \|e verfasserin \|4 aut
700	0		\|a J. Sunil \|e verfasserin \|4 aut
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allfields	10.1016/j.rico.2024.100379 doi (DE-627)DOAJ095677429 (DE-599)DOAJb10404fb5956455d927ed6bc295f9eec DE-627 ger DE-627 rakwb eng T57-57.97 Haewon Byeon verfasserin aut A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against. Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods Santosh Kumar verfasserin aut Divya Mahajan verfasserin aut K. Haribabu verfasserin aut M. Sivaprakash verfasserin aut Harshal Patil verfasserin aut J. Sunil verfasserin aut In Results in Control and Optimization Elsevier, 2021 14(2024), Seite 100379- (DE-627)1744665966 26667207 nnns volume:14 year:2024 pages:100379- https://doi.org/10.1016/j.rico.2024.100379 kostenfrei https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec kostenfrei http://www.sciencedirect.com/science/article/pii/S2666720724000092 kostenfrei https://doaj.org/toc/2666-7207 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 14 2024 100379-
spelling	10.1016/j.rico.2024.100379 doi (DE-627)DOAJ095677429 (DE-599)DOAJb10404fb5956455d927ed6bc295f9eec DE-627 ger DE-627 rakwb eng T57-57.97 Haewon Byeon verfasserin aut A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against. Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods Santosh Kumar verfasserin aut Divya Mahajan verfasserin aut K. Haribabu verfasserin aut M. Sivaprakash verfasserin aut Harshal Patil verfasserin aut J. Sunil verfasserin aut In Results in Control and Optimization Elsevier, 2021 14(2024), Seite 100379- (DE-627)1744665966 26667207 nnns volume:14 year:2024 pages:100379- https://doi.org/10.1016/j.rico.2024.100379 kostenfrei https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec kostenfrei http://www.sciencedirect.com/science/article/pii/S2666720724000092 kostenfrei https://doaj.org/toc/2666-7207 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 14 2024 100379-
allfields_unstemmed	10.1016/j.rico.2024.100379 doi (DE-627)DOAJ095677429 (DE-599)DOAJb10404fb5956455d927ed6bc295f9eec DE-627 ger DE-627 rakwb eng T57-57.97 Haewon Byeon verfasserin aut A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against. Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods Santosh Kumar verfasserin aut Divya Mahajan verfasserin aut K. Haribabu verfasserin aut M. Sivaprakash verfasserin aut Harshal Patil verfasserin aut J. Sunil verfasserin aut In Results in Control and Optimization Elsevier, 2021 14(2024), Seite 100379- (DE-627)1744665966 26667207 nnns volume:14 year:2024 pages:100379- https://doi.org/10.1016/j.rico.2024.100379 kostenfrei https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec kostenfrei http://www.sciencedirect.com/science/article/pii/S2666720724000092 kostenfrei https://doaj.org/toc/2666-7207 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 14 2024 100379-
allfieldsGer	10.1016/j.rico.2024.100379 doi (DE-627)DOAJ095677429 (DE-599)DOAJb10404fb5956455d927ed6bc295f9eec DE-627 ger DE-627 rakwb eng T57-57.97 Haewon Byeon verfasserin aut A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against. Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods Santosh Kumar verfasserin aut Divya Mahajan verfasserin aut K. Haribabu verfasserin aut M. Sivaprakash verfasserin aut Harshal Patil verfasserin aut J. Sunil verfasserin aut In Results in Control and Optimization Elsevier, 2021 14(2024), Seite 100379- (DE-627)1744665966 26667207 nnns volume:14 year:2024 pages:100379- https://doi.org/10.1016/j.rico.2024.100379 kostenfrei https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec kostenfrei http://www.sciencedirect.com/science/article/pii/S2666720724000092 kostenfrei https://doaj.org/toc/2666-7207 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 14 2024 100379-
allfieldsSound	10.1016/j.rico.2024.100379 doi (DE-627)DOAJ095677429 (DE-599)DOAJb10404fb5956455d927ed6bc295f9eec DE-627 ger DE-627 rakwb eng T57-57.97 Haewon Byeon verfasserin aut A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against. Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods Santosh Kumar verfasserin aut Divya Mahajan verfasserin aut K. Haribabu verfasserin aut M. Sivaprakash verfasserin aut Harshal Patil verfasserin aut J. Sunil verfasserin aut In Results in Control and Optimization Elsevier, 2021 14(2024), Seite 100379- (DE-627)1744665966 26667207 nnns volume:14 year:2024 pages:100379- https://doi.org/10.1016/j.rico.2024.100379 kostenfrei https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec kostenfrei http://www.sciencedirect.com/science/article/pii/S2666720724000092 kostenfrei https://doaj.org/toc/2666-7207 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 14 2024 100379-
language	English
source	In Results in Control and Optimization 14(2024), Seite 100379- volume:14 year:2024 pages:100379-
sourceStr	In Results in Control and Optimization 14(2024), Seite 100379- volume:14 year:2024 pages:100379-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN Applied mathematics. Quantitative methods
isfreeaccess_bool	true
container_title	Results in Control and Optimization
authorswithroles_txt_mv	Haewon Byeon @@aut@@ Santosh Kumar @@aut@@ Divya Mahajan @@aut@@ K. Haribabu @@aut@@ M. Sivaprakash @@aut@@ Harshal Patil @@aut@@ J. Sunil @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
hierarchy_top_id	1744665966
id	DOAJ095677429
language_de	englisch
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callnumber-first	T - Technology
author	Haewon Byeon
spellingShingle	Haewon Byeon misc T57-57.97 misc Hybrid path finder misc Vortex search misc Improved dwarf mongoose optimization misc Underwater WSN misc Applied mathematics. Quantitative methods A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN
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topic_title	T57-57.97 A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN Hybrid path finder Vortex search Improved dwarf mongoose optimization Underwater WSN
topic	misc T57-57.97 misc Hybrid path finder misc Vortex search misc Improved dwarf mongoose optimization misc Underwater WSN misc Applied mathematics. Quantitative methods
topic_unstemmed	misc T57-57.97 misc Hybrid path finder misc Vortex search misc Improved dwarf mongoose optimization misc Underwater WSN misc Applied mathematics. Quantitative methods
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title	A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN
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title_full	A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN
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author_browse	Haewon Byeon Santosh Kumar Divya Mahajan K. Haribabu M. Sivaprakash Harshal Patil J. Sunil
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title_sort	hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in uwsn
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title_auth	A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN
abstract	In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.
abstractGer	In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.
abstract_unstemmed	In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.
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title_short	A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN
url	https://doi.org/10.1016/j.rico.2024.100379 https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec http://www.sciencedirect.com/science/article/pii/S2666720724000092 https://doaj.org/toc/2666-7207
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author2	Santosh Kumar Divya Mahajan K. Haribabu M. Sivaprakash Harshal Patil J. Sunil
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Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hybrid path finder</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Vortex search</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Improved dwarf mongoose optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Underwater WSN</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Applied mathematics. 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Sunil</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Results in Control and Optimization</subfield><subfield code="d">Elsevier, 2021</subfield><subfield code="g">14(2024), Seite 100379-</subfield><subfield code="w">(DE-627)1744665966</subfield><subfield code="x">26667207</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:14</subfield><subfield code="g">year:2024</subfield><subfield code="g">pages:100379-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.rico.2024.100379</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/b10404fb5956455d927ed6bc295f9eec</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" 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A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN

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