Knowledge Engineering and Data Science
Vol 1, No 2 (2018)

Energy Efficiency Metrics of University Data Centers

Leonel Hernandez (University Institution ITSA)
Genett Jimenez (Institución Universitaria ITSA, Carrera 45 # 48 – 31, Barranquilla, Colombia)
Piedad Marchena (Institución Universitaria ITSA, Carrera 45 # 48 – 31, Barranquilla, Colombia)



Article Info

Publish Date
23 Aug 2018

Abstract

The data centers are fundamental pieces in the network and computing infrastructure, and evidently today more than ever they are relevant. Since they support the processing, analysis, assurance of the data generated in the network and by the applications in the cloud, which every day increases its volume thanks to technologies such as Internet of Things, Virtualization, and cloud computing, among others. Precisely the management of this large volume of information makes the data centers consume a lot of energy, generating great concern to owners and administrators. Green Data Centers offer a solution to this problem, reducing the impact produced by the data centers in the environment, through the monitoring and control of these. The metrics are the tools that allow us to measure in our case the energy efficiency of the data center and evaluate if it is friendly to the environment. These metrics will be applied to the data centers of the ITSA University Institution, Barranquilla and Soledad campus, and the analysis of these will be carried out. In previous research, the most common metric (PUE) was analyzed to measure the efficiency of the data centers, to verify if the University's data center is friendly to the environment. It is planned to extend this study by carrying out an analysis of several metrics to conclude which is the most efficient and which allows defining the guidelines to update or convert the data center in a friendly environment. 

Copyrights © 2018






Journal Info

Abbrev

keds

Publisher

Subject

Computer Science & IT Engineering

Description

Knowledge Engineering and Data Science (2597-4637), KEDS, brings together researchers, industry practitioners, and potential users, to promote collaborations, exchange ideas and practices, discuss new opportunities, and investigate analytics frameworks on data-driven and knowledge base systems. ...