Amelioration of task scheduling in cloud computing using crow search algorithm

Cloud computing is a dynamic and diverse environment across different geographical locations. In reality, it consists of a vast number of tasks and computing resources. In cloud, task scheduling algorithm is the core player which identifies the suitable virtual machine (VM) for a task. The task scheduling algorithm is responsible for reducing the makespan of the schedule. In recent years, nature-inspired algorithms are applied to task scheduling which performs better than conventional algorithms. In this paper, crow search algorithm (CSA) is proposed for task scheduling in cloud. It is inspired from the food collecting habits of crow. In reality, the crow keeps on eyeing on its other mates to find a better food source than current food source. In this way, the CSA finds a suitable VM for the task and minimizes the makespan. Experiments are carried out using cloudsim to measure the performance of the CSA along with Min–Min and ant algorithms. Simulation results reveal that CSA algorithm performs better compared to Min–Min and Ant algorithms.