Machine Learning and Deep Learning Algorithms for Green Computing

Abstract

Green computing is an innovative approach to making computer systems environmentally friendly, energy-efficient, and low in carbon emissions. It uses advanced techniques from machine learning and deep learning to optimize real-time resource allocation, reducing energy consumption. This approach enhances workload patterns and uses methods like convolutional and recurrent neural networks to enhance architectural efficiency. The integration of ML and DL techniques allows for accurate temperature forecasting and alternative cooling strategies. Despite challenges, the synergistic fusion of ML and DL algorithmic software with green computing holds great promise for reducing energy consumption and enhancing environmental sustainability.