A Comparative Analytics for Dynamic Load Balancing Mechanisms Intended to Improve Task Scheduling in Cloud Computing

Cloud computing is a term that encompasses a worldwide linked network of computer resources, including server infrastructure, connections, apps, equipment, and firmware. A good usage technique for resource utilization is load balancing. The practice of reassigning the total load to the individual nodes in a particular network is known as task distribution in the cloud. Since no specific research is carried out to perform comparative analytics in terms of different parameters of scheduling of task-based algorithms, it is crucial to develop a consistent comparison mechanism among them. Distribution of tasks is the primary concern of crucial elements that boost performance and optimize resource usage. FCFS, SJF, OLB, and GPA are the scheduling algorithms that are explored. This study surveys the various scheduling methods employed by cloud service providers. There are many scheduling approaches available to optimize performance and minimize execution time.