Wireless Sensor Network (WSN) Model Targeting Energy Efficient Wireless Sensor Networks Node Coverage

With the rise of the Internet of Things, the application fields of wireless sensor networks (WSN) continue to expand. From agriculture to urban infrastructure monitoring, application requirements in various fields are increasing. The research focuses on designing and improving energy-efficient cover...

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Bibliographic Details
Published in:IEEE access 2024, Vol.12, p.27596-27610
Main Authors: Jia, Runliang, Zhang, Haiyu
Format: Article
Language:English
Subjects:
Algorithms
Data transmission
Energy consumption
Energy efficiency
grey wolf algorithm
Internet of Things
Maintenance costs
Monitoring
monitoring area
node coverage
Nodes
Optimization
Resource utilization
Routing
routing protocol
Routing protocols
Sensors
Sustainable development
Wireless sensor network
Wireless sensor networks
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Summary:With the rise of the Internet of Things, the application fields of wireless sensor networks (WSN) continue to expand. From agriculture to urban infrastructure monitoring, application requirements in various fields are increasing. The research focuses on designing and improving energy-efficient coverage methods for wireless sensor network nodes, with the goal of improving energy efficiency and data transmission reliability. Through detailed research and analysis of hierarchical and flat routing protocols, the article explores how to ensure that each monitoring point is covered by at least one sensor node by designing an energy-saving sensor network node coverage model. At the same time, the study explores an energy-efficient coverage method based on the improved gray wolf algorithm, aiming to optimize the deployment of sensor nodes and enhance the effectiveness of node coverage. Research results show that the algorithm performs significantly in network coverage optimization and achieves 100% coverage of monitoring target points. Under the 30-dimensional condition, the improved gray wolf algorithm shows excellent average performance and the smallest standard deviation. When the number of nodes is 40, compared with other algorithms, the improved gray wolf algorithm improves the coverage rate by 5.08% and achieves 100% coverage performance in a more energy-saving manner. Research on the exploration of energy-saving wireless sensor network models will help to better meet the needs of future intelligent monitoring and control, improve resource utilization efficiency, reduce maintenance costs, and promote the sustainable development of wireless sensor networks.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3365511