Crow Search Algorithm (CSA) for Task-Scheduling in Cloud Computing

Abstract

A significant breakthrough in the IT sector has emerged in cloud computing. Utilizing cloud facilities as services has made this approach possible for users. In the world of cloud computing, scheduling tasks are a major issue. A scheduler of tasks has required in cloud computing to efficiently assign the tasks to the appropriate virtual machines (VMs). Through the use of a task scheduler, tasks in cloud computing are properly mapped to the right VMs to reduce make-span time. To overcome the scheduling issue in cloud computing, numerous scholars in the research have employed evolutionary algorithms. For scheduling tasks on the cloud, the CSA (crow search algorithm) is suggested in this research. It takes its cues from crows' propensity for gathering food. In truth, the crow is constantly keeping an eye on its fellow birds to discover a stronger source of food beyond its present one. By doing this, the CSA reduces the make-span and locates a VM that is appropriate for the task. Cloud-sim is used in studies to evaluate the effectiveness of the CSA in comparison with the ACO and Min-Min algorithms. The outcomes of the simulation show that the CSA algorithm outperforms the ACO and Min-Min algorithms.