Electricity Consumption and Cost Prediction for Cloud Computing

Cloud computing's rapid ascent in the IT industry simplifies tasks by eliminating the need for physical hardware, with services managed by cloud providers operating electricity-powered computers. The design and upkeep of these facilities depend on affordable, consistent electrical power. However, cloud centers face challenges in reducing energy consumption, highlighted by recent spikes in electricity expenses. To address this, optimizing data placement and node scheduling is crucial. This article introduces an approach using Random Forest and XGBoost models to facilitate storage offloading, predict electricity pricing trends, and reduce energy expenditure in data centers. The proposed work aims to enhance energy awareness, enabling other management tools to make informed, energy-efficient decisions and reduce electricity consumption, lowering costs for cloud providers and minimizing environmental impact.