A model of energy-awareness predictor to improve the energy efficiency
- Authors
- Kim, Svetlana; Yoon, 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.
- Files in This Item
-
Go to Link
- Appears in
Collections - ICT융합공학부 > IT공학전공 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.