NHARSO-IWSN: A Novel Hybridized Adaptive-Network-Based Fuzzy Inference System With Reptile Search Optimization Algorithm Based Routing Protocol for Internet of Things-Enabled Wireless Sensor Networks

Advances in Internet of Things (IoT) technologies will facilitate smart cities and industrial applications. IoT-based applications rely on Wireless Sensor Networks (WSNs) for data transmission and sensing. Battery power is limited in IoT-enabled WSNs (IWSN) due to their irreplaceable nature. Existing clustering schemes could not mitigate control packet overhead due to the extra energy consumption required for processing data, gathering data, and forwarding tasks. The proposed routing protocol uses a hybrid adaptive network-based fuzzy inference system with reptile search optimization (NHARSO) to determine the optimal routing path between cluster heads (CH) and base stations of Internet of Things-enabled Wireless Sensor Networks (IWSN). Afterward, the proposed NHARSO-IWSN protocol can detect faults in IWSN, such as sensing, residual energy, and communication. Simulation results indicate that NHARSO-IWSN achieves a lower energy consumption of 0.005 J and a higher detection accuracy of 99.11% compared to existing protocols.