Efficient Workload Distribution for Sustainable Server Utilization in Cloud Data Centers

Cloud service providers offer flexible infrastructure scaling options, allowing users to adjust resources based on their requirements and pay only for what they use. This paper proposes an approach to efficiently distribute workloads across host machines within a data center environment. This work proposes the concept of skewness as a measure of server utilization, identifying underutilized servers. When a server is found to be underused, its workload is redistributed to other host machines, enabling the underutilized server to be idled and potentially shut down. This strategy not only optimizes server utilization but also contributes to green computing initiatives by reducing power consumption and carbon footprint. Through Simulation, we demonstrate the effectiveness of our approach in achieving both scalability and sustainability in cloud computing environments.