Machine Learning for Load Forecasting in a Green Data Center

Since green cloud computing became a significant advancement in the world of computing in the past few years, its user base has been consistently expanding. Companies are adding more hosts and servers to their data centers to keep up with the ever-growing demand for cloud services. So, these huge servers use a lot of energy, raise costs, and put out a significant amount of greenhouse gasses. Also, even devices that are not being used use a lot of energy. Also, when CPU use reaches its peak, it is hard to keep node clusters running and use less energy. In this paper, we propose machine learning models to determine the minimum execution time. These models reduce the work done by machines and make sure that requests are managed correctly in data centers. Therefore, the purpose of this study is to present an effective strategy for the management of energy with a focus on the sustainability of green cloud data centers.