A Novel XG-Boost Approach for Electricity Load Balancing and Demand Prediction

Cloud computing quickly gains traction in IT because it simplifies computing without requiring physical hardware. Instead, cloud service providers host these services. These companies have many energy-consuming computers and servers, so their design and maintenance rely on a consistent, low-cost power supply. Clouds are voracious consumers of energy. Given recent increases in electricity costs, minimising data centre energy use is one of the primary challenges in planning and implementing appropriate data placement and node scheduling to offload or transfer storage. Present an Extreme Gradient Boosting (XG-Boost) model for unloading or moving storage, forecasting power prices, and lowering data centre energy costs. The proposed method outperforms conventional approaches significantly.