A Review of Diverse Optimization Strategies for Task Scheduling in Cloud Computing

Applications requiring large amounts of computation are increasingly being run on heterogeneous distributed computing platforms. When it comes to pay-per-use computing and storage resources, cloud computing is a paradigm for on-demand provisioning. Data centers are responsible for managing these resources, which are dynamically assigned to users based on criteria including availability, demand, and quality standards. Cloud computing manages a wide range of virtualized resources. Clients use hundreds of virtual resources for each job. By reducing time loss, task scheduling seeks to maximise performance. Several studies have been conducted in this area, resulting in an extensive list of tactics and measurements specific to cloud environments. In this study, scheduling approaches are examined, along with related problems and constraints. Arranged according to techniques, uses, and metrics based on parameters, the review of literature offers a comprehensive perspective. It also indicates potential directions for cloud- computing scheduling research.