Optimal Radius for Enhanced Lifetime in IoT Using Hybridization of Rider and Grey Wolf Optimization

Connecting all devices through the Internet is now practical via the Internet of Things (IoT). IoT is characterized by using smart and self-configuring objects that can interact with each other via global network infrastructure. Clustering is the promising technique that effectively works on the enhancement of network lifetime. This paper intends to introduce a new clustering technique, where the selection of cluster head is done by a new hybrid algorithm termed Over taker Assisted Wolf Update (OA-WU), which hybrids the concept of Rider Optimization Algorithm (ROA) and Grey Wolf Optimization algorithm (GWO). This cluster head selection has been dealt with certain constraints like (i) Energy (ii) Distance and (iii) Cluster Radius. The proposed OA-WU performance is compared with the traditional methods with respect to alive node analysis, cost function analysis and energy analysis. The results demonstrate that the proposed OA-WU algorithm adequately improves the energy conservation and convergence rate in a minuscule period.