Optimal Task Scheduling in the Cloud Computing using Artificial Intelligence Algorithms

Abstract

In recent years, online small business across the world has increased exponentially. To run the business, resources are required in terms of hardware and software. Thus, buying all these resources is overpriced for the small business owner. In order to overcome this issue, in the current scenario, the main business owner shares their resources on the cloud network, and small business owners access these resources according to their requirements and pay to the main business owner according to the period of time they are accessing the resources. Besides that, a number of requests are generated from different locations to access these resources and managing these requests in an appropriate way, therefore, task scheduling is imperative for the same. So, task scheduling technique access these requests and rearrange in an appropriate way and users have to wait minimum for accessing their resources. First come first serve (FCFS), min-min, shortest job first (SJF), and max-min are the popular task scheduling techniques in the literature. These task scheduling techniques are highly effective when the number of tasks are less but their performance degrades when tasks are exponentially increased. In order to overcome this limitation, metaheuristic algorithms which is a sub-field of artificial intelligence algorithms have been used for task scheduling. newline