American Zebra Optimization Algorithm-based Clustering Protocol for Reliable Data Routing in Internet of Things

In Internet of Things (IoT), devices connect and function in wireless mode for gathering information from the sorrounding environment and performing reactive decision-making. But network lifetime of these IoT devices completely depends on how limited energy resources are optimized during normal functioning such that impactful performance measures get improved eventually. Though quantifiable amount of research works using Swarm Intelligent (SI) algorithms are contributed to the literature for handling and achieving energy efficiency of IoT nodes deployed in the network, there is still a scope of improvement in optimization and routing mechanisms. In this paper, American Zebra Optimization Algorithm-based Clustering Protocol (AZOACP) is proposed for attaining energy efficiency of sensor nodes such that longer network lifetime with reliable data routing is guaranteed in IoT. The adopted American Zebra Optimization Algorithm (AZOA) possesses maximized capability of exploration with rapid rate of convergence such that better Cluster Heads (CHs) are selected for achieving better energy efficiency during routing. It further adopts the factors of initial energy level of nodes, energy availability, distance between CHs and distance between each sensor node and sink, and number of neighbours for selecting CHs in the network. The simulation results of the proposed AZOACP confirm better stability period, network lifetime, throughput and number of alive nodes compared to baseline approaches considered for comparison.