Open AccessPower Usage Efficiency (PUE) Optimization with Counterpointing Machine Learning Techniques for Data Center Temperatures
Author(s) -
Rajendra Kumar,
Sunil Kumar Khatri,
Mario José Diván
Publication year - 2021
Publication title -
international journal of mathematical, engineering and management sciences
Language(s) - English
Resource type - Journals
ISSN - 2455-7749
DOI - 10.33889/ijmems.2021.6.6.095
Subject(s) - data center , power (physics) , computer science , range (aeronautics) , center (category theory) , work (physics) , reliability engineering , engineering , mechanical engineering , operating system , chemistry , physics , quantum mechanics , crystallography , aerospace engineering
The rapid increase in the IT infrastructure has led to demands in more Data Center Space & Power to fulfil the Information and Communication Technology (ICT) services hosting requirements. Due to this, more electrical power is being consumed in Data Centers therefore Data Center power & cooling management has become quite an important and challenging task. Direct impacting aspects affecting the power energy of data centers are power and commensurate cooling losses. It is difficult to optimise the Power Usage Efficiency (PUE) of the Data Center using conventional methods which essentially need knowledge of each Data Center facility and specific equipment and its working. Hence, a novel optimization approach is necessary to optimise the power and cooling in the data center. This research work is performed by varying the temperature in the data center through a machine learning-based linear regression optimization technique. From the research, the ideal temperature is identified with high accuracy based on the prediction technique evolved out of the available data. With the proposed model, the PUE of the data center can be easily analysed and predicted based on temperature changes maintained in the Data Center. As the temperature is raised from 19.73 oC to 21.17 oC, then the cooling load is decreased in the range 607 KW to 414 KW. From the result, maintaining the temperature at the optimum value significantly improves the Data Center PUE and same time saves power within the permissible limits.