Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique
This research focuses on Wireless Sensor Networks (WSNs) and proposes a three-phase approach to achieve energy-efficient routing. The approach consists of node deployment using Voronoi diagrams, clustering, and Cluster Head (CH) selection using energy-efficient game theory, and a routing strategy ba...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-01-01
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| Series: | Automatika |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2024.2431750 |
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| author | S. Sangeetha T. Aruldoss Albert Victoire M. Premkumar R. Sowmya |
| author_facet | S. Sangeetha T. Aruldoss Albert Victoire M. Premkumar R. Sowmya |
| author_sort | S. Sangeetha |
| collection | DOAJ |
| description | This research focuses on Wireless Sensor Networks (WSNs) and proposes a three-phase approach to achieve energy-efficient routing. The approach consists of node deployment using Voronoi diagrams, clustering, and Cluster Head (CH) selection using energy-efficient game theory, and a routing strategy based on Improved Pelican Optimization (ImPe) segment routing. Random deployment of sensor nodes in WSNs can lead to coverage issues, and hence, in order to address this, Voronoi-based node deployment is employed to ensure uniform and balanced coverage of the monitoring area. An energy-efficient game theory-based approach is used for CH selection by considering the energy levels to select CHs for enhancing network longevity. The proposed routing mechanism utilizes segment routing, which provides deterministic routing paths from CHs to the sink (Base Station). Segment routing eliminates the need for route discovery and maintenance, making it energy-efficient. The ImPe algorithm that works on the characteristics of pelican search agents is employed to choose the optimal segment path for information sharing. The assessment based on delay, network lifetime, packet delivery ratio, residual energy, throughput, communication overhead, and energy utilization acquired the values of 2.57, 98.59, 98.29, 0.98, 238.51, 7.71, and 0.02 respectively. |
| format | Article |
| id | doaj-art-053b21ce5b5a41018e34559c21513f83 |
| institution | Kabale University |
| issn | 0005-1144 1848-3380 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Automatika |
| spelling | doaj-art-053b21ce5b5a41018e34559c21513f832025-01-30T05:18:09ZengTaylor & Francis GroupAutomatika0005-11441848-33802025-01-01661244210.1080/00051144.2024.2431750Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering techniqueS. Sangeetha0T. Aruldoss Albert Victoire1M. Premkumar2R. Sowmya3Computer Science and Engineering, Karpagam College of Engineering, Coimbatore, IndiaElectrical and Electronics Engineering, Anna University Regional Campus, Coimbatore, IndiaDepartment of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, IndiaDepartment of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaThis research focuses on Wireless Sensor Networks (WSNs) and proposes a three-phase approach to achieve energy-efficient routing. The approach consists of node deployment using Voronoi diagrams, clustering, and Cluster Head (CH) selection using energy-efficient game theory, and a routing strategy based on Improved Pelican Optimization (ImPe) segment routing. Random deployment of sensor nodes in WSNs can lead to coverage issues, and hence, in order to address this, Voronoi-based node deployment is employed to ensure uniform and balanced coverage of the monitoring area. An energy-efficient game theory-based approach is used for CH selection by considering the energy levels to select CHs for enhancing network longevity. The proposed routing mechanism utilizes segment routing, which provides deterministic routing paths from CHs to the sink (Base Station). Segment routing eliminates the need for route discovery and maintenance, making it energy-efficient. The ImPe algorithm that works on the characteristics of pelican search agents is employed to choose the optimal segment path for information sharing. The assessment based on delay, network lifetime, packet delivery ratio, residual energy, throughput, communication overhead, and energy utilization acquired the values of 2.57, 98.59, 98.29, 0.98, 238.51, 7.71, and 0.02 respectively.https://www.tandfonline.com/doi/10.1080/00051144.2024.2431750Segment routinggame theory-based clusteringhybrid optimizationimproved pelican algorithmwireless sensor networks |
| spellingShingle | S. Sangeetha T. Aruldoss Albert Victoire M. Premkumar R. Sowmya Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique Automatika Segment routing game theory-based clustering hybrid optimization improved pelican algorithm wireless sensor networks |
| title | Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique |
| title_full | Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique |
| title_fullStr | Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique |
| title_full_unstemmed | Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique |
| title_short | Segment routing for WSN using hybrid optimization with energy-efficient game theory-based clustering technique |
| title_sort | segment routing for wsn using hybrid optimization with energy efficient game theory based clustering technique |
| topic | Segment routing game theory-based clustering hybrid optimization improved pelican algorithm wireless sensor networks |
| url | https://www.tandfonline.com/doi/10.1080/00051144.2024.2431750 |
| work_keys_str_mv | AT ssangeetha segmentroutingforwsnusinghybridoptimizationwithenergyefficientgametheorybasedclusteringtechnique AT taruldossalbertvictoire segmentroutingforwsnusinghybridoptimizationwithenergyefficientgametheorybasedclusteringtechnique AT mpremkumar segmentroutingforwsnusinghybridoptimizationwithenergyefficientgametheorybasedclusteringtechnique AT rsowmya segmentroutingforwsnusinghybridoptimizationwithenergyefficientgametheorybasedclusteringtechnique |