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A model of energy-awareness predictor to improve the energy efficiency

Authors
Kim, SvetlanaYoon, Yong-Ik
Issue Date
May-2017
Publisher
Springer Verlag
Keywords
Context-aware; Energy efficiency; Energy-awareness predictor; Tensor factorization
Citation
Lecture Notes in Electrical Engineering, v.448, pp 656 - 662
Pages
7
Journal Title
Lecture Notes in Electrical Engineering
Volume
448
Start Page
656
End Page
662
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/8932
DOI
10.1007/978-981-10-5041-1_105
ISSN
1876-1100
Abstract
The data centers contribute to high operational costs and electrical energy will be consumed in enormous amounts. One of the most complex challenges of energy consumption is power management. Many different methods have been applied in order to reduce energy consumption. In this paper, we propose the architecture framework focuses on analyzing the EAP (Energy-Awareness Predictor) to improve the energy efficiency. Through analysis and various integrated sensor devices, the EAP architecture framework can understanding of the consumption patterns and can better controlling of the major energy consuming. Based on inputs independent variables (value of external and internal environmental) is prediction and implement refrigeration and process control, optimization and energy management. © Springer Nature Singapore Pte Ltd. 2017.
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