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
N1 - Funding Information:
ACKNOWLEDGMENT This work was partially supported by MEXT/JSPS KAKENHI Grant (B) Number JP16H04455 and JP17H01739, through the funding received from SECOM Science and Technology Foundation, from MLIT Grant for development of advanced technology in housing and buildings, by R&D project “Design of Information and Communication Platform for Future Smart Community Services” by the Ministry of Internal Affairs and Communications of Japan, and from Keio University Global Smart Society Creation Project Research.
Publisher Copyright:
© 2017 IEEE.
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
T3 - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
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.
T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Y2 - 29 October 2017 through 1 November 2017
ER -
