Efficient energy utilization based on task distribution and cooling airflow management in a data center

Yusuke Nakajo, Tomomichi Noguchi, Hiroaki Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7171-7176
Number of pages6
Volume2017-January
ISBN (Electronic)9781538611272
DOIs
Publication statusPublished - 2017 Dec 15
Event43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China
Duration: 2017 Oct 292017 Nov 1

Other

Other43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
CountryChina
CityBeijing
Period17/10/2917/11/1

Fingerprint

Data Center
Energy Efficient
Energy Consumption
Cooling
Energy utilization
Control System
Control systems
Rack
Internet of Things
Task Allocation
HTTP
Smartphones
Cloud computing
Energy
Cloud Computing
Managers
Servers
Server
Internet
Tend

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

Nakajo, Y., Noguchi, T., & Nishi, H. (2017). Efficient energy utilization based on task distribution and cooling airflow management in a data center. In Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society (Vol. 2017-January, pp. 7171-7176). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2017.8217255

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 proceedingConference contribution

Nakajo, Y, Noguchi, T & Nishi, H 2017, Efficient energy utilization based on task distribution and cooling airflow management in a data center. in Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 7171-7176, 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Beijing, China, 17/10/29. https://doi.org/10.1109/IECON.2017.8217255
Nakajo Y, Noguchi T, Nishi H. Efficient energy utilization based on task distribution and cooling airflow management in a data center. In 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 https://doi.org/10.1109/IECON.2017.8217255
Nakajo, Yusuke ; Noguchi, Tomomichi ; Nishi, Hiroaki. / Efficient energy utilization based on task distribution and cooling airflow management in a data center. Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 7171-7176
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