• DocumentCode
    644380
  • Title

    BFEPM: Best Fit Energy Prediction Modeling Based on CPU Utilization

  • Author

    Xiao Zhang ; Jianjun Lu ; Xiao Qin

  • Author_Institution
    Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2013
  • fDate
    17-19 July 2013
  • Firstpage
    41
  • Lastpage
    49
  • Abstract
    Energy cost becomes a major part of data center operational cost. Computer system consume more power when it runs under high workload. Many past studies focused on how to predict power consumption by performance counters. Some models retrieve performance counters from chips. Some models query performance counters from OS. Most of these researches were verified on several machines and claimed their models were accurate under the test. We found different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark result. We illustrate how to use benchmark result to find a best fit model. Then we validate the viability and effectiveness of model on all published results. At last, we apply the best fit model on two different machines to estimate the real-time energy consumption. The results show our model can get better results than single model.
  • Keywords
    computer centres; energy consumption; power aware computing; BFEPM modeling; CPU utilization; best fit energy prediction modeling; data center operational cost; energy cost; performance counters; power consumption benchmark result; realtime energy consumption estimation; Benchmark testing; Computational modeling; Energy consumption; Mathematical model; Power demand; Radiation detectors; Servers; data center management; energy consumption mode; green computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Architecture and Storage (NAS), 2013 IEEE Eighth International Conference on
  • Conference_Location
    Xi´an
  • Type

    conf

  • DOI
    10.1109/NAS.2013.12
  • Filename
    6665344