Energy-Efficient Task Consolidation for Cloud Data Center

Energy-Efficient Task Consolidation for Cloud Data Center

Sudhansu Shekhar Patra (School of Computer Application, KIIT University, Bhubaneswar, India)
Copyright: © 2018 |Pages: 26
DOI: 10.4018/IJCAC.2018010106

Abstract

Energy saving in a Cloud Computing environment is a multidimensional challenge, which can directly decrease the in-use costs and carbon dioxide emission, while raising the system consistency. The process of maximizing the cloud computing resource utilization which brings many benefits such as better use of resources, rationalization of maintenance, IT service customization, QoS and reliable services, etc., is known as task consolidation. This article suggests the energy saving with task consolidation, by minimizing the number of unused resources in a cloud computing environment. In this article, various task consolidation algorithms such as MinIncreaseinEnergy, MaxUtilECTC, NoIdleMachineECTC, and NoIdleMachineMaxUtil are presented aims to optimize energy consumption of cloud data center. The outcomes have shown that the suggested algorithms surpass the existing ECTC and FCFSMaxUtil, MaxMaxUtil algorithms in terms of the CPU utilization and energy consumption.
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2. Energy Efficiency In Cloud Computing

In the last years cloud computing has become more and more popular. This increase in popularity of cloud services results in higher resource demands on the providers end. More resources mean more energy consumption and thus higher electricity bills. Google consumed 2.68 million megawatt hours of electricity in 2011. In 2016 google said it had proved it could cut total energy use at its data centers by 15% by deploying machine learning from DeepMind, the British AI company it bought in 2014 for about £400m.

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