Abstract
With the recent emergence of smartphones, cloud computing, and the Internet of Things (IoT), our society has become more dependent on the Internet. In these circumstances, increasing energy consumption in data centers is becoming a crucial problem worldwide and data center managers are required to run them efficiently in terms of energy consumption. This study aims to reduce cooling airflow energy by achieving appropriate task distribution and adding a shutter control system, which reduces the energy consumption of an air-conditioner. In most cases, servers tend to be unnecessarily cooled at low temperatures, even when their exhaust temperatures are not high. Our proposed method solves this problem by using shutter control and introducing a task allocation method. We built an experimental rack model and implemented our proposed control system, validating it with a real HTTP data request. The results show that our experimental system reduces the cooling airflow energy by 4.4%.
| Original language | English |
|---|---|
| Title of host publication | Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 7171-7176 |
| Number of pages | 6 |
| Volume | 2017-January |
| ISBN (Electronic) | 9781538611272 |
| DOIs | |
| Publication status | Published - 2017 Dec 15 |
| Event | 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China Duration: 2017 Oct 29 → 2017 Nov 1 |
Other
| Other | 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 17/10/29 → 17/11/1 |
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Keywords
- air flow control
- cooling efficiency
- data center
- load balancing
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Control and Optimization
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
Cite this
Efficient energy utilization based on task distribution and cooling airflow management in a data center. / Nakajo, Yusuke; Noguchi, Tomomichi; Nishi, Hiroaki.
Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 7171-7176.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Efficient energy utilization based on task distribution and cooling airflow management in a data center
AU - Nakajo, Yusuke
AU - Noguchi, Tomomichi
AU - Nishi, Hiroaki
PY - 2017/12/15
Y1 - 2017/12/15
N2 - With the recent emergence of smartphones, cloud computing, and the Internet of Things (IoT), our society has become more dependent on the Internet. In these circumstances, increasing energy consumption in data centers is becoming a crucial problem worldwide and data center managers are required to run them efficiently in terms of energy consumption. This study aims to reduce cooling airflow energy by achieving appropriate task distribution and adding a shutter control system, which reduces the energy consumption of an air-conditioner. In most cases, servers tend to be unnecessarily cooled at low temperatures, even when their exhaust temperatures are not high. Our proposed method solves this problem by using shutter control and introducing a task allocation method. We built an experimental rack model and implemented our proposed control system, validating it with a real HTTP data request. The results show that our experimental system reduces the cooling airflow energy by 4.4%.
AB - With the recent emergence of smartphones, cloud computing, and the Internet of Things (IoT), our society has become more dependent on the Internet. In these circumstances, increasing energy consumption in data centers is becoming a crucial problem worldwide and data center managers are required to run them efficiently in terms of energy consumption. This study aims to reduce cooling airflow energy by achieving appropriate task distribution and adding a shutter control system, which reduces the energy consumption of an air-conditioner. In most cases, servers tend to be unnecessarily cooled at low temperatures, even when their exhaust temperatures are not high. Our proposed method solves this problem by using shutter control and introducing a task allocation method. We built an experimental rack model and implemented our proposed control system, validating it with a real HTTP data request. The results show that our experimental system reduces the cooling airflow energy by 4.4%.
KW - air flow control
KW - cooling efficiency
KW - data center
KW - load balancing
UR - http://www.scopus.com/inward/record.url?scp=85046652696&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046652696&partnerID=8YFLogxK
U2 - 10.1109/IECON.2017.8217255
DO - 10.1109/IECON.2017.8217255
M3 - Conference contribution
AN - SCOPUS:85046652696
VL - 2017-January
SP - 7171
EP - 7176
BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PB - Institute of Electrical and Electronics Engineers Inc.
ER -