Power-Efficient Cluster Head Selection in Wireless Sensor Networks using Whale and Seagull Algorithms

WSN includes deployed sensors. These small sensor nodes have energy limits since their batteries can't be replaced. Collect, transmit, and transfer data to the base station. Data transmission depletes WSN energy. Clustering is an efficient WSN data transport technique. Whale Optimization (WSOA) combines a seagull method with a global issue to meet global optimization concerns. The suggested technique helps choose based on residual node energy and nearby nodes, energy-aware cluster heads energy into consideration. Lifetime, energy economy, throughput, and stability of the recommended algorithm are tested. The hybrid metaheuristic's performance is compared to LEACH. The suggested approach outperforms others in residual energy, network longevity, and stability period.