An Energy-Efficient Hybrid Clustering Technique (EEHCT) for IoT-Based Multilevel Heterogeneous Wireless Sensor Networks

Internet-of-Things (IoT)-based Heterogeneous Wireless Sensor Network (HWSN) has emerged as a prevalent technology that plays significant role in developing various human-centric applications. Like wireless sensor network (WSN), energy is also the most crucial resource IoT-based HWSN. The researchers have proposed many works to achieve energy-efficient operations by minimizing usage. A vast proportion of these emphasize using clustering approach, which proved its worth great extent. However, schemes require repeated formation clusters incurring amount nodes’ process. protocol design such varies with changing levels heterogeneity. In this work, hybrid scheme- An Energy-Efficient Hybrid Clustering Technique (EEHCT) been for HWSN minimizes consumption clusters’ and distributes load evenly irrespective heterogeneity level prolong lifetime. It appropriately utilizes dynamic static strategies formulate load-balanced network. EEHCT establishes supremacy over state-of-the-art via an extensive set simulations experimentation terms multiple performance metrics like stability, throughput, Like, it achieves gain up 90.27% respect lifetime peers standard operating conditions under varying configurations. addition quantitative analysis, statistical analysis provided demonstrate energy-balanced through scheme.