Paper Abstract and Keywords |
Presentation |
2016-03-04 11:40
GA-based task assignment and air conditioner setting for reducing data center power consumption. Takaaki Deguchi (Osaka Univ.), Koji Suganuma (NAIST), Yuya Tarutani, Go Hasegawa, Yutaka Nakamura (Osaka Univ.), Takumi Tamura, Kazuhiro Matsuda (NTT-AT), Morito Matsuoka (Osaka Univ.) NS2015-219 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this report, we propose a data center energy management architecture focusing on coordinated operation among various equipment in a data center.
A data center control system is constructed based on the proposed architecture.
The proposed system is evaluated in our data center testbed.
Evaluation results show that the proposed system reduces the data center total power consumption by 6.3 % compared with a setting for reducing server power consumption and by 5.9 % compared with that for reducing air conditioner power consumption. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Data center / Power consumption reduction / Coordinated control system / Machine learning / Genetic algorithm / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 483, NS2015-219, pp. 297-302, March 2016. |
Paper # |
NS2015-219 |
Date of Issue |
2016-02-25 (NS) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
NS2015-219 |