Task Scheduling Optimization in the Cloud Using Improved Heuristic Algorithm

Abstract

Cloud Computing has become the most efficient and reliable technology in today’s era. Almost every organization and individual depend upon this technology to perform their task and even for storage purpose. As the number of users is growing, the complexity of this technology has also increased massively. Thus, for reliable and efficient use of cloud technology, the tasks, infrastructures, and load must be balanced in the system. Among different methods, one of the ways to efficiently manage the complexity of the system is task scheduling. Task scheduling helps to optimize CPU utilization and make the tasks done with minimum loss. Also, there are many task-scheduling algorithms which have been proposed and implemented to date. Every algorithm has its pros and cons too. Thus, this project aims to implement the proposed improved heuristic (B-Sufferage) Algorithm to schedule tasks in a cloud environment and compare the result with the existing PSO and Min-Min Task Scheduling Algorithm. The B-Sufferage Algorithm depends upon the sufferage value to schedule a particular task on a particular VM. The required infrastructure has been set up using CloudSim 3.0.3 and the implementation has been carried out by configuring respective algorithms. As a result, it has been found that the B-Sufferage algorithm in task scheduling works better than the existing one. Thus, the result has been compared based on metrics like makespan, resource utilization, turn-around time, and waiting time where there is a significant difference for scheduling tasks using this B-Sufferage; an improved heuristic algorithm.