A Systematic Investigation of Workflow Scheduling Techniques in the Cloud

Abstract

The primary participants in the cloud technology context are cloud users and service providers. This setting comprises data centers, servers, agents, and virtual machines. The supplier's resources are rented to the cloud customer for varying loads. Since cloud services are so ubiquitous, most scientists use them to run their workflow applications. Scientific applications are workflow challenges that are huge and complex and require higher processing power. The cloud satisfies the workflow requirements of massive availability and enhanced computational power. For the cloud computing system to operate well, scheduling is one of the most recent research topics. This study examines several task-scheduling methods currently in use that are based on various criteria. This work will help the investigators to gain a better understanding of task scheduling techniques. The result of the investigation is tabulated with their performance parameter metrics like response time, energy efficiency, fault tolerance, and efficient resource usage.