Energy-Efficient Data Aggregation Techniques in Wireless Sensor Networks

Wireless sensor networks (WSNs) have been extensively employed and developed due to their numerous applications like medicine, military, environment monitoring, and industry. WSNs enable remote interaction among number of sensor nodes and have applications in environmental monitoring and communication node tracking. However, the optimization of energy consumption in WSNs is a significant challenge since sensor nodes usually rely on limited energy sources such as batteries. As WSNs become more common, minimizing data transmission and processing becomes essential. Therefore, the data aggregation methods are important for reducing energy consumption. These methods considerably decrease redundant data transmission, resulting in considerable energy savings. Several energy-efficient data aggregation approaches such as cluster-based aggregation are widely utilized in WSNs-based system. The proposed method based on two strategies, namely clustering and duty cycling to minimize the power consumption and maximizing the operational lifetime of the network. Low-Energy Adaptive Clustering Hierarchy (LEACH) is a common clustering-based designed for WSNs to minimize energy consumption and optimized network lifetime. But the major issue in LEACH method is network instability due to random selection of cluster head which can result in non-uniform energy consumption and early death of cluster heads. Particle Swarm Optimization (PSO) is an optimization technique assisted by the nature, used for solving complex problems. But the major drawback of PSO is its sensitivity to parameter settings, which can affect solution quality. The proposed scheme (advanced PSO-Improved LEACH) optimizes networks by employing the LEACH method combined PSO with an upgraded selection of cluster head. This modification called K-times cluster head selection enhancement (K-ILEACH) is suggested for networks. Simulation results show that the number of operational active nodes in a network is increased by 35% and accompanied by a 16.6% increase in energy consumption overhead compared to existing LEACH methods.