Optimal Fault Tolerant Based Clustering Approach for Energy-Level Routing in IoT-Based Wireless Sensor Networks

The Integration of IoT-based applications into wireless sensor networks for enhanced data collection and monitoring. Wireless sensor networks (WSNs) must use a variety of tactics to lower overall energy usage in order to achieve energy efficiency. To extend the lifespan of a network, fault tolerance and energy balancing must be given equal priority. Although finding the quickest route to the Base Station (BS) is still important, clustering is acknowledged as an important energy-saving method. The energy used by cluster heads (CHs) in cluster-based WSNs to collect and aggregate data from member sensor nodes might increase due to failures brought on by extreme stress. The choice of CHs greatly affects the energy consumption of sensor nodes, increasing the lifetime of WSNs. An intelligent energy-saving technique called “An Energy-Efficient Unequal fault tolerant clustering approach,” or “OPT-FL-CL,” promotes Particle Swarm Optimization (PSO). With the use of PSO, the method presents an ideal MCH-MDA selection process that finds the two cluster nodes most suitable for acting as the MCH and the Master Data Aggregator (MDA). The chosen MCH gathers data from cluster members, while the MDA receives data from the MCH prior to sending it to the BS, minimizing MCH overhead. Time division multiple access (EE-TDMA) energy-efficient scheduling controls overhead during large-scale data transfers. Simulations will show that the suggested solutions outperform the existing approaches in a number of performance criteria.