A New Adaptive Energy-Aware Job Scheduling in Cloud Computing

Abstract

In the last decade, with the significant growth of the calculation and data concerns over energy use and carbon dioxide emissions caused by the servers have increased. Various scheduling algorithms have been created all of which attempt to reduce the execution time of tasks and have not paid enough attention to reduce energy consumption. Other scheduling algorithms try to reduce the makespan and the energy consumption simultaneously that are known as the energy-aware scheduling algorithms. The algorithm presented in this article schedules the tasks with a focus on reducing makespan and energy consumption. The proposed method provides a new scheduling algorithm using four factors of communication between tasks, the distance between nodes, virtual machines’ status and energy consumption forecasts to reduce makespan and energy consumption. The purpose of this scheduling algorithm is to reduce the displacement between the nodes and optimize VMs execution that using the analytical hierarchy process (AHP) the best decision is made for task implementation.