Resource Scheduling Algorithms in Cloud Computing: A Big Picture

With the increase in digital footprint, a computing model that can process the data parallel without increasing the overall cost has been sought. For this, many computing models have been proposed. Cloud computing is one of them that provides a good solution for a variety of applications. By utilizing a network of remote servers, cloud computing manages and processes a variety of data over virtualized resources making scheduling of tasks critical for performance. In the cloud, to completely execute the task, several virtualized resources may be required. Thus, making manual scheduling an unfeasible solution. For maximizing resource utilization and minimizing the makespan of the task, task scheduling schedules tasks in cloud computing. Various researchers have proposed their research for scheduling tasks in past. The task scheduling in the cloud over virtual resources can be either static and dynamic in nature. This paper presents a comparative analysis of FIFS, RR, SJF, Priority, Max-Min, EDF scheduling algorithms in cloud platforms on parameters such as response time, makespan, throughput, and energy efficiency and tries to identify an algorithm that is most suitable for the cloud environment. CloudSim is used as the simulator tool For analyzing the performance of various algorithms and the results are discussed in detail.