Title: A power saver scheduling algorithm using DVFS and DNS techniques in cloud computing data centres

Authors: Saleh Atiewi; Salman Yussof; Mohd Ezanee Bin Rusli; Mutasem Zalloum

Addresses: College of Computer Science and Information Technology, Tenaga National University, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia ' College of Computer Science and Information Technology, Tenaga National University, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia ' College of Computer Science and Information Technology, Tenaga National University, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia ' SENECA Company, Maka Street, 11732, Amman, Jordan

Abstract: Cloud computing is a fascinating and profitable area in modern distributed computing. Aside from providing millions of users the means to use offered services through their own computers, terminals, and mobile devices, cloud computing presents an environment with low cost, simple user interface, and low power consumption by employing server virtualisation in its offered services (e.g., Infrastructure as a Service). The pool of virtual machines found in a cloud computing data centre (DC) must run through an efficient task scheduling algorithm to achieve resource utilisation and good quality of service, thus ensuring the positive effect of low energy consumption in the cloud computing environment. In this paper, we present an energy-efficient scheduling algorithm for a cloud computing DC using the dynamic voltage frequency scaling technique. The proposed scheduling algorithm can efficiently reduce the energy consumption for executing jobs by increasing resource utilisation. GreenCloud simulator is used to simulate our algorithm. Experimental results show that, compared with other algorithms, our algorithm can increase server utilisation, reduce energy consumption, and reduce execution time.

Keywords: DVFS; DNS; virtual machine; data centre; cloud computing; power consumption.

DOI: 10.1504/IJGUC.2018.095439

International Journal of Grid and Utility Computing, 2018 Vol.9 No.4, pp.385 - 395

Received: 05 Jan 2017
Accepted: 10 Aug 2017
Published online: 04 Oct 2018 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article