Energy Aware Management for Tasks Scheduling Using Dynamic Voltage and Frequency Scaling Techniques in Cloud Data Centers - A Case Study in the Ports and Maritime Organization - Hamed Ghorbani; Behnam Barzegar; Mousa Nazari (مدیریت مهندسی و رایانش نرم)
The issue of energy management is considered as one of the main concerns in cloud computing systems to support the rapid growth of data centers and computing Becomes. Dynamic voltage and frequency scaling strategies focus on reducing energy consumption as well as optimizing efficiency parameters. In this paper, we present an energy-conscious and reliable three-step scheduling algorithm called ERADVFS using the DVFS technique on a cloud center processor with dynamic voltage and frequency scaling capability. The goal of this algorithm is to consume the least amount of energy while ensuring reliability and limited task scheduling. In the first step, we determine the worst execution time of each task in each virtual machine of that type on each frequency level. Then in the next step, we divide the deadline for doing the work between the tasks. Finally, by assigning the DVFS technique, we assign tasks to the best virtual machine. The main idea in selecting a virtual machine is to take advantage of the extended amount of runtime to reduce the frequency of the virtual machine.