Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management

Abstract

Cloud computing has become more prevalent in recent years. Cloud computing is the use of centralized computer resources. Users may utilize these resources to finish calculations, and the cloud computing center will provide the user with the program’s processing results. Cloud computing is helpful for both consumer and business users. Users may save computing expenditures by avoiding the need to acquire several PCs by investing in a cloud server. China Economic News Network reports that the country’s cloud computing market is worth 209.1 billion yuan. China’s more established cloud service providers include Huawei Cloud, Baidu Cloud, Ali Cloud, etc. In light of this, this study suggests a novel method for handling challenging issues related to scheduling and managing cloud computing resources using machine learning optimization approaches. This study provides a comprehensive solution, including optimization techniques like deep learning and genetic algorithms, to improve system performance and efficiency and thus bring breakthroughs and progress in cloud computing resource management. Rational allocation of resources plays a crucial role in cloud computing. The study thoroughly examines issues like low resource utilization and unbalanced load in the cloud environment. Users come in order at the cloud computing center, which has restricted cloud resources for resource allocation. Each user requests a specified quantity of cloud resources to be used by the cloud computing center at a given time.

DOI - https://doi.org/10.65525/SVUP.9788199956087.2026.55-65