Optimizing hybrid metaheuristic algorithm with cluster head to improve performance metrics on the IoT

The Internet of Things (IoT) has subsequently been applied to a variety sectors, including smart grids, farming, weather prediction, power generation, wastewater treatment, and so on. So if the enormous promise in wide range applications, there still are certain areas where it may be improved. Designers had focused our present research on reducing energy consumption devices IoT networks, which will result longer network lifetime. far more suitable Cluster Head (CH) throughout system is determined this study optimize consumption. Whale Optimization Algorithm (WOA) with Evolutionary (EA) indeed mixed meta-heuristic algorithm used during suggested study. Various quantifiable metrics, adult nodes, workload, temperatures, remaining energy, target value, were utilized groups. method then contrasted several cutting-edge optimization techniques, Artificial Bee Colony method, Neural Network, Adapted Gravity Simulated annealing. findings show that hybrid outperforms conventional methods.