A Systematic Analysis on Task Scheduling Algorithms for Resource Allocation of Virtual Machines on Cloud Computing Environments

Abstract

In the emerging field of technology and science, cloud computing is an effective IT service model providing computing services like database storage, network, analytics and software to the consumer and user over the internet. The Cloud computing archetype offers various benefits over the traditional self-hosting computing solution, though it has the critical challenge of assigning the task to the computing resource. Task scheduling is a prominent issue for all cloud providers and having an efficient task scheduling algorithm is a must for processing. Plentiful task scheduling algorithms are implemented with different techniques and defined by various performance factors like increasing throughput, minimizing time and makespan. This paper outlines a survey on existing task scheduling algorithms in the cloud platform. A set of contexts and scenarios are created to examine and contrast how different task scheduling algorithm work. Task scheduling algorithms, namely FCFS, Short Job First (SJF), Round Robin, Priority algorithm, Modified Short Job First, Enhanced Round Robin and Genetic algorithm, are investigated in this paper based on performance metrics like makespan, turnaround time, No. of Virtual Machines and cloudlets.