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

Abstract

Cloud computing refers to a network of computing resources (servers, networks, applications, hardware, and software) interconnected globally. 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 there is now no specific research 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. FCFS, SJF, OLB, and GPA are the scheduling algorithms that are explored. Distribution of tasks is the main concern of crucial elements that boosts performance and optimizes resource usage. This study surveys the various scheduling methods employed by cloud service providers. There are so many scheduling approaches available to optimize performance and minimize execution time. It also discusses the security challenges in the cloud according to infrastructure and services.