Deep Learning Based Load Balancing in Cloud Computing: A Survey

Deep learning has become a potent tool for solving challenging problems across a variety of professions. It presents intriguing approaches to optimize resource utilization and boost system performance in the context of load balancing in cloud computing. This review paper offers a comprehensive examination of current deep learning-based load balancing methods, highlighting their advantages, disadvantages, and possible uses. We give a comprehensive analysis of the current state of deep learning-based load balancing based on a thorough review of research publications and projects. The results provide insight into how well deep learning models handle load-balancing problems. This assessment lays the foundation for future research by recognizing research needs and understanding the existing environment. The information provided will help researchers and professionals create novel strategies to improve load distribution and increase the effectiveness of cloud computing systems.