Energy-efficient task distribution using neural network temperature prediction in a data center

Minato Omori, Yusuke Nakajo, Minami Yoda, Yogendra Joshi, Hiroaki Nishi

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

Abstract

The growing demand for computing resources leads to a serious problem of excessive energy consumption in data centers. In recent studies, energy consumption of both computing and cooling equipment is drawing attention. For improving the energy efficiency of cooling equipment such as computer room air conditioners (CRACs), it is neccesary to predict temperatures in data centers and to optimize thermal management in data centers. In this study, we propose a temperature prediction method for servers in a data center using a neural network. We used the prediction result for distributing task targeting temperature-based load balancing. First, we conducted an experiment in a real data center to evaluate the prediction accuracy of the proposed method. We then simulated task distribution based on the predicted temperatures and compared the maximum CPU temperature with a non-predictive approach. The results indicated that the proposed method can reduce future CPU temperatures successfully compared to the non-predictive approach, though in exchange for high computational cost.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1429-1434
Number of pages6
ISBN (Electronic)9781728129273
DOIs
Publication statusPublished - 2019 Jul
Event17th IEEE International Conference on Industrial Informatics, INDIN 2019 - Helsinki-Espoo, Finland
Duration: 2019 Jul 222019 Jul 25

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
Volume2019-July
ISSN (Print)1935-4576

Conference

Conference17th IEEE International Conference on Industrial Informatics, INDIN 2019
CountryFinland
CityHelsinki-Espoo
Period19/7/2219/7/25

Keywords

  • Data center
  • Load balancing
  • Neural network
  • Temperature prediction
  • Thermal management

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Omori, M., Nakajo, Y., Yoda, M., Joshi, Y., & Nishi, H. (2019). Energy-efficient task distribution using neural network temperature prediction in a data center. In Proceedings - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019 (pp. 1429-1434). [8972035] (IEEE International Conference on Industrial Informatics (INDIN); Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INDIN41052.2019.8972035