A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm
Wireless Sensor Networks (WSNs) are crucial components of modern technology, supporting applications like healthcare, industrial automation, and environmental monitoring. This research aims to design intelligent and adaptive sensor networks by integrating metaheuristics with node coverage optimizati...
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Elsevier
2024-12-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024013987 |
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| author | V. Saravanan Indhumathi G Ramya Palaniappan Narayanasamy P M. Hema Kumar K. Sreekanth Navaneethan S |
| author_facet | V. Saravanan Indhumathi G Ramya Palaniappan Narayanasamy P M. Hema Kumar K. Sreekanth Navaneethan S |
| author_sort | V. Saravanan |
| collection | DOAJ |
| description | Wireless Sensor Networks (WSNs) are crucial components of modern technology, supporting applications like healthcare, industrial automation, and environmental monitoring. This research aims to design intelligent and adaptive sensor networks by integrating metaheuristics with node coverage optimization in WSNs. By incorporating metaheuristics and optimizing node coverage, WSNs can become more resilient and robust, leading to the development of self-adapting, self-organizing networks capable of efficiently covering dynamic and diverse environments. This research introduces the Walrus Optimization Algorithm for Node Coverage Enhancement in WSNs, called the WaOA-NCEWSN technique. The primary goal of this technique is to optimize the coverage of a target region using a limited number of Sensor Nodes (SNs) and by improving their placement. The WaOA is inspired by walrus behaviours like feeding, migrating, breeding, escaping, roosting, and gathering in response to environmental signals. The WaOA-NCEWSN technique uses an objective function that defines the coverage ratio, representing the maximum probability of coverage in a 2D-WSN monitoring area. Comparative analysis with other models using 50, 75, 100, and 200 nodes shows that the WaOA-NCEWSN technique performs better. The compilation times for the WaOA-NCEWSN technique are 5.14s, 6.48s, 6.54s, and 7.47s for 50, 75, 100, and 200 nodes, respectively. Experimental results indicate that the WaOA-NCEWSN technique offers superior coverage performance compared to other models. |
| format | Article |
| id | doaj-art-9566b183e6484bfb8f02b7a6c3be176c |
| institution | OA Journals |
| issn | 2590-1230 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-9566b183e6484bfb8f02b7a6c3be176c2025-08-20T01:58:16ZengElsevierResults in Engineering2590-12302024-12-012410314310.1016/j.rineng.2024.103143A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithmV. Saravanan0Indhumathi G1Ramya Palaniappan2Narayanasamy P3M. Hema Kumar4K. Sreekanth5Navaneethan S6Department of Nano Electronics Materials and Sensors, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu, IndiaDepartment of ECE, Rajalakshmi Engineering College, Chennai, Tamilnadu, IndiaDepartment of Computer Science & Engineering, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh, IndiaDepartment of Mathematics, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamilnadu, IndiaDepartment of ECE, Sona College of Technology, Salem, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, IndiaDepartment of ECE, Saveetha Engineering College, Chennai, Tamilnadu, India; Corresponding author.Wireless Sensor Networks (WSNs) are crucial components of modern technology, supporting applications like healthcare, industrial automation, and environmental monitoring. This research aims to design intelligent and adaptive sensor networks by integrating metaheuristics with node coverage optimization in WSNs. By incorporating metaheuristics and optimizing node coverage, WSNs can become more resilient and robust, leading to the development of self-adapting, self-organizing networks capable of efficiently covering dynamic and diverse environments. This research introduces the Walrus Optimization Algorithm for Node Coverage Enhancement in WSNs, called the WaOA-NCEWSN technique. The primary goal of this technique is to optimize the coverage of a target region using a limited number of Sensor Nodes (SNs) and by improving their placement. The WaOA is inspired by walrus behaviours like feeding, migrating, breeding, escaping, roosting, and gathering in response to environmental signals. The WaOA-NCEWSN technique uses an objective function that defines the coverage ratio, representing the maximum probability of coverage in a 2D-WSN monitoring area. Comparative analysis with other models using 50, 75, 100, and 200 nodes shows that the WaOA-NCEWSN technique performs better. The compilation times for the WaOA-NCEWSN technique are 5.14s, 6.48s, 6.54s, and 7.47s for 50, 75, 100, and 200 nodes, respectively. Experimental results indicate that the WaOA-NCEWSN technique offers superior coverage performance compared to other models.http://www.sciencedirect.com/science/article/pii/S2590123024013987Node coverageOptimization problemWireless sensor networkPerformance estimationWalrus optimization algorithm |
| spellingShingle | V. Saravanan Indhumathi G Ramya Palaniappan Narayanasamy P M. Hema Kumar K. Sreekanth Navaneethan S A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm Results in Engineering Node coverage Optimization problem Wireless sensor network Performance estimation Walrus optimization algorithm |
| title | A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| title_full | A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| title_fullStr | A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| title_full_unstemmed | A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| title_short | A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| title_sort | novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm |
| topic | Node coverage Optimization problem Wireless sensor network Performance estimation Walrus optimization algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024013987 |
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