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.
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Acknowledgement
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R2718-16-0004-0001002) supervised by the IITP (National IT Industry Promotion Agency).
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Kim, S., Yoon, YI. (2017). A Model of Energy-Awareness Predictor to Improve the Energy Efficiency. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_105
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DOI: https://doi.org/10.1007/978-981-10-5041-1_105
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