Task scheduling algorithms for energy optimization in cloud environment: a comprehensive review

Cloud computing is very popular because of its unique features such as scalability, elasticity, on-demand service, and security. A large number of tasks are performed simultaneously in a cloud system, and an effective task scheduler is needed to achieve better efficiency of the cloud system. Task scheduling algorithm should determine a sequence of execution of tasks to meet the requirements of the user in terms of Quality of Service (QoS) factors (e.g., execution time and cost). The key issue in recent task scheduling is energy efficiency since it reduces cost and satisfies the standard parameter in green computing. The most important aim of this paper is a comparative analysis of 67 scheduling methods in the cloud system to minimize energy consumption during task scheduling. This work allows the reader to choose the right scheduling algorithm that optimizes energy properly, given the existing problems and limitations. In addition, we have divided the algorithms into three categories: heuristic-based task scheduling, meta-heuristic-based task scheduling, and other task scheduling algorithms. The advantages and disadvantages of the proposed algorithms are also described, and finally, future research areas and further developments in this field are presented.

Automated summary

This paper focuses on the task scheduling methods in cloud systems, with a particular emphasis on energy efficiency. It conducts a comparative analysis of 67 scheduling methods, describing the advantages and disadvantages of the proposed algorithms, and presents future research areas and further developments in this field.