Nature inspired Task Scheduling Algorithm for Improving Quality of Service in Cloud Environment

Abstract

Cloud computing is becoming the most promising and life-changing technology in today’s world. It is a highly virtualized platform, which captivates the attention of varied users to meet their demands for resources. It has made the availability of resources very convenient, which makes it even easier to implement services on these platforms. The healthcare system is moving its infrastructure to the Cloud to take the maximum benefit of this technology. It undertakes the execution of tasks or jobs to meet the requests for these services. In order to deploy health services to the cloud without any hindrance, it is vital to handle task scheduling. In this paper, a cloud-based framework for health system has been proposed. Which is utilize the Ant Colony Optimization algorithm for optimizing priority of the task scheduling, by focused on providing classification for every user with various level to prioritize their tasks while organizing the jobs in the task queue. The Java-based tool cloudsim is used to implement the task scheduling algorithms. In this paper traditional algorithms are also implemented and record the result based on various parameters. The proposed algorithm is compared with other traditional algorithms as First Come First Serve (FCFS) algorithm and Round Robin (RR) algorithm. The obtained outcomes show the proposed algorithm based on Ant Colony Optimization gives better results than traditional algorithm in every aspect.