Optimizing Cloud-Based IoT Architectures with an Energy-Sensitive Load Balancing Algorithm for Enhanced Resource Utilization and Network Efficiency

Cloud computing, which provides virtualized computing resources online, has become increasingly popular. Effective load balancing (LB) is essential for distributing dynamic workloads among cloud systems and ensuring equitable resource sharing, which prevents server overloads. This study presents a customized cloud-based load balancer algorithm designed for IoT network protocols, evaluating the demands of virtual and physical host machines in cloud environments. The algorithm manages loads within cloud-based IoT architectures to enhance energy efficiency and improve network response times while integrating seamlessly with existing frameworks. Utilizing proportional sharing, the method migrates heavily loaded virtual machines to less strained physical hosts. Key characteristics, including memory specifications, CPU utilization, power consumption, and SLA violation management, are considered. The Updated Energy-Sensitive Balancing Load Algorithm (ESBL) is developed to analyze IoT sensor data and, compared to older approaches, optimizes load balancing and other critical parameters. The proposed load balancer significantly improves resource utilization and network efficiency, ultimately optimizing IoT communication in cloud computing environments.