Efficient Load Balancing Algorithms for Edge Computing in IoT Environments

This study investigates the accuracy of load balancing calculations in terms of edge computing for IoT. The paper compared four main calculations, namely Round Robin (RR), Weighted Round Robin (WRR), Least Connections (LC) and Ant Colony Optimization ratings in an reproduced edge computing atmosphere. As for the study, it focused on efficiency improvements of asset utilization as well as reducing inactivity and enhancing reasonableness. Weighted Round Robin showed that the predominant execution came about with an astonishing 25% decrease in idleness as compared to a depiction of noncapacity aware task load distribution. The Slightest Associations also showed extraordinary outcomes, achieving 20% decrease in idle period and demonstrated that it could be flexible with workloads. While flexible, Ant Colony Optimization demonstrated an inability to achieve steady variation improvements related with parameter tuning ranging from 15% toward 30%. The discoveries emphasize the significance of calculation choice based on the particular prerequisites of IoT edge situations.