Research of Coverage Optimization Strategy Based on Improved Northern Goshawk Algorithm
To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. In the covera...
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Veröffentlicht in: | IEEE sensors journal 2024-08, Vol.24 (16), p.26668-26681 |
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creator | Yao, Yindi Song, Xiaoxiao Zhao, Bozhan Tian, Yuying Yang, Ying Yang, Maoduo |
description | To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability. |
doi_str_mv | 10.1109/JSEN.2024.3419174 |
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In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2024.3419174</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive algorithms ; Coverage optimization ; Energy consumption ; Force ; Global optimization ; hole repair ; Local optimization ; Maintenance engineering ; Monitoring ; Nodes ; northern goshawk (NGO) algorithm ; Obstacle avoidance ; Optimization ; Particle swarm optimization ; Repair ; Sensors ; Stability ; video sensor networks (VSNs)</subject><ispartof>IEEE sensors journal, 2024-08, Vol.24 (16), p.26668-26681</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c176t-ab0a1dfeb8c446c93c4819925834acb7cc2fcae945878b885a0ac14e650af0a03</cites><orcidid>0009-0000-2347-1081 ; 0009-0007-7046-3499 ; 0000-0002-3586-6774 ; 0009-0005-8274-2933 ; 0000-0003-0711-9090</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10582836$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,27929,27930,54763</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10582836$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yao, Yindi</creatorcontrib><creatorcontrib>Song, Xiaoxiao</creatorcontrib><creatorcontrib>Zhao, Bozhan</creatorcontrib><creatorcontrib>Tian, Yuying</creatorcontrib><creatorcontrib>Yang, Ying</creatorcontrib><creatorcontrib>Yang, Maoduo</creatorcontrib><title>Research of Coverage Optimization Strategy Based on Improved Northern Goshawk Algorithm</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description>To solve the problems of low monitoring area coverage, high network energy consumption, and network instability in video sensor networks (VSNs), a novel node deployment strategy is proposed, which is divided into coverage optimization stage and coverage hole detection and repair stage. 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The simulation results show that INGO-CO proposed in this article can effectively improve the network coverage by only adjusting sensing direction. After detecting and repairing the coverage hole, the node deployment strategy effectively reduce the network energy consumption and enhance the network stability.</description><subject>Adaptive algorithms</subject><subject>Coverage optimization</subject><subject>Energy consumption</subject><subject>Force</subject><subject>Global optimization</subject><subject>hole repair</subject><subject>Local optimization</subject><subject>Maintenance engineering</subject><subject>Monitoring</subject><subject>Nodes</subject><subject>northern goshawk (NGO) algorithm</subject><subject>Obstacle avoidance</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>Repair</subject><subject>Sensors</subject><subject>Stability</subject><subject>video sensor networks (VSNs)</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkMFOAjEQhhujiYg-gImHJp4X22272z0iUcQQSESjt2a2dNlFoNgWDT693cDB00wm3z8z-RC6pqRHKSnunmcPk15KUt5jnBY05yeoQ4WQSWzladszknCWf5yjC--XhNAiF3kHvb8Yb8DpGtsKD-y3cbAweLoNzbr5hdDYDZ4FB8Es9vgevJnjOBmtty6iczyxLtTGbfDQ-hp-PnF_tbCuCfX6Ep1VsPLm6li76O3x4XXwlIynw9GgP040zbOQQEmAzitTSs15pgumuaRFkQrJOOgy1zqtNJiCC5nLUkoBBDTlJhMEKgKEddHtYW_86GtnfFBLu3ObeFIxEmNUcCkjRQ-UdtZ7Zyq1dc0a3F5Rolp_qvWnWn_q6C9mbg6ZxhjzjxcylSxjf8AHbRc</recordid><startdate>20240815</startdate><enddate>20240815</enddate><creator>Yao, Yindi</creator><creator>Song, Xiaoxiao</creator><creator>Zhao, Bozhan</creator><creator>Tian, Yuying</creator><creator>Yang, Ying</creator><creator>Yang, Maoduo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In the coverage optimization stage, this article proposed an improved northern goshawk coverage optimization (INGO-CO) algorithm. First, the adaptive inertia weight strategy and the improved Levy flight strategy are used to improve the convergence speed and the ability to jump out of the local optimal. Second, to balance the ability of global optimization and local optimization, the exponentially decaying hunting radius is introduced. Finally, the virtual-force-based obstacle avoidance strategy was added to avoid invalid coverage of nodes. In the phase of hole detection and repair, a sleeping strategy of redundant nodes based on the coverage matrix of neighbor nodes is proposed to find the nodes that can sleep to reduce network energy consumption. Then, a method of repairing holes based on maximum length was proposed, which used dormant nodes to repair holes to ensure network stability. 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subjects | Adaptive algorithms Coverage optimization Energy consumption Force Global optimization hole repair Local optimization Maintenance engineering Monitoring Nodes northern goshawk (NGO) algorithm Obstacle avoidance Optimization Particle swarm optimization Repair Sensors Stability video sensor networks (VSNs) |
title | Research of Coverage Optimization Strategy Based on Improved Northern Goshawk Algorithm |
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