Energy Aware Cluster Based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks

In order to prevent the overloading, the routing algorithm aids in building productive paths both within and between clusters. When sending information from the source Internet of Things (IoT) device to a Base Station (BS), not all IoT devices are utilized in the path. We introduced an energy aware cluster-based routing in this paper, in which Improved Fuzzy C-means (IFCM) model plays a major role in clustering initially. Meanwhile, the clustering procedure considers the factors like energy and distance. Subsequent to the clustering process, optimal routing will be takes place by a new hybrid optimization algorithm named Custom Honey Badger and Coot Optimization (CHBCO) that combines the models like Honey badger optimization and Coot optimization model, respectively. For routing, the model considers the constraints like Energy as well as link quality. Also, this model establishes the fault tolerance method, which ensures that the network will continue to operate normally even in the situation of a Cluster Head (CH) failure. During this, the cluster members switch to another CH. The performance of proposed CHBCO based routing model is compared over existing models with respect to convergence rate, distance evaluation, energy, alive nodes, distance, normalized energy and link quality under various scenarios.