GWO-EFUCA: Grey Wolf Optimisation and Fuzzy Logic based Unequal Clustering and Routing protocol for sustainable WSN-based Internet of Things

Abstract With the ever-growing application of Wireless Sensor Networks (WSN)-based Internet of Things (IoT), it has gained enormous attention in the public and research domains. The energy constraint of WSN limits its applicability. In the paper, we have proposed a hybrid of Grey Wolf Optimisation along with Fuzzy Logic (FL) for energy-efficient Cluster Head (CH) selection, cluster formation, and cost-effective routing which improves Quality of Service (QoS) that can enhance the applicability of WSN in the diverse domains of IoT. The proposed work is simulated, and performance assessment is done on the basis of QoS metrics namely FND, HND, throughput, average energy, average node load and latency. The obtained results exhibit significant enhancement in the network lifetime with an enhanced stability period, higher throughput, reduced latency, and lessen traffic load and load-balanced network towards its comparative making it suitable for wide applicability in WSN based IoT.