A SURVERY OF OPTIMIZATION TECHNIQUES FOR ENERGY-EFFICIENT CLOUD CONTAINER SCHEDULING

Abstract

Light virtualization techniques known as cloud computing containers have shown to be promising in providing cloud services. This is because it is scalable, portable and simply decorated in a variety of ways, especially for cloud computing MicroD services. Due to the adoptable properties of the cloud content nature of cloud containers, some of the schedulers are extremely important for improving performance and reducing costs. This study classifies planning strategies for four groups based on optimization methods that use schedules, mathematical linear approaches, heuristic approaches, metaheuristic approaches, and machine learning methods. This paper focuses on a variety of optimization techniques to reduce power consumption and resource use