Weight possibilistic fuzzy C-means energy-efficient clustering (WPFCM-EEC) and fuzzy osprey optimisation algorithm (FOOA) for IoT-WSN

The wireless sensor network (WSN) is a key component of IoT systems. Wireless sensing nodes in WSNs have energy limitation issues since replacing or recharging their batteries and upgrading their transmitting and memory capacity is difficult. Thus, clustering algorithms efficiently save node energy and lengthen IoT-based WSN lifespan. These protocols cluster nodes to communicate with a BS at a shorter distance. However, clustering structure concerns hurt current clustering methods. In this research, the weight possibilistic fuzzy C-means-energy efficient clustering (WPFCM-EEC) protocol is presented to extend IoT-based WSN lifetime. The WPFCM-EEC protocol has three parts. First, the optimal cluster count and overlap are established. Next, a weight possibilistic fuzzy C means algorithm creates balanced and static clusters to ensure sensor node energy balance. A unique Cluster Head selection and rotation algorithm that combines the fuzzy osprey optimisation algorithm (FOOA) with a rotation mechanism selects CH in optimal locations by rotating the cluster head function across cluster members. The methods are tested in MATLAB R2023a. Protocol evaluation indicators include first node dies (FND), last node dies (LND), weighted first node dies (WFND), half of the nodes dies (HND), average energy consumption, and throughput.