AEELD: An Adaptive Energy-Efficient Strategy Based on Location Density Awareness in Wireless Sensor Networks
Cheng Zhang, Zhan Wen, Demao Xiong, Wenzao Li · IEEE Systems Journal · 2025
Wireless sensor networks (WSNs), the fundamental sensing layer of the Internet of Things, are widely deployed in environmental monitoring, smart agriculture, and other fields. However, sensor nodes rely on limited battery power, and the intertwined issues of uneven energy consumption, node failure, and data loss in complex environments severely constrain network reliability and lifetime. To address these challenges, this article proposes an adaptive energy-efficient strategy based on location density awareness in wireless sensor networks (AEELD) protocol. This protocol introduces and optimizes the application of the clustering by fast search and find of density peaks (CFSFDPs) algorithm in WSNs, enhancing the cluster head selection process through improvements to the CFSFDP algorithm. In addition, an adaptive data transmission round adjustment mechanism is designed to dynamically regulate the number of transmission rounds based on the results of each clustering process. Furthermore, a cluster head state optimization mechanism is proposed, categorizing the energy levels of cluster heads. Data transmission is activated only when the energy meets specific requirements, effectively preventing network data loss and improving the utilization of limited node energy. Experimental results demonstrate that, compared to low-energy adaptive clustering hierarchy (LEACH), improved LEACH, K-means algorithm supported by LEACH-KMe, and balanced residual energy-LEACH protocols, AEELD exhibits superior performance in key metrics such as network lifetime, total effective data transmission volume, and energy consumption balance among nodes, validating its effectiveness in practical deployments.