• DocumentCode
    3141302
  • Title

    Estimating mobile application energy consumption using program analysis

  • Author

    Shuai Hao ; Ding Li ; Halfond, William G. J. ; Govindan, Ramesh

  • Author_Institution
    Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2013
  • fDate
    18-26 May 2013
  • Firstpage
    92
  • Lastpage
    101
  • Abstract
    Optimizing the energy efficiency of mobile applications can greatly increase user satisfaction. However, developers lack viable techniques for estimating the energy consumption of their applications. This paper proposes a new approach that is both lightweight in terms of its developer requirements and provides fine-grained estimates of energy consumption at the code level. It achieves this using a novel combination of program analysis and per-instruction energy modeling. In evaluation, our approach is able to estimate energy consumption to within 10% of the ground truth for a set of mobile applications from the Google Play store. Additionally, it provides useful and meaningful feedback to developers that helps them to understand application energy consumption behavior.
  • Keywords
    mobile computing; program diagnostics; Google Play store; energy consumption estimation; mobile application energy consumption; per-instruction energy modeling; program analysis; user satisfaction; Cost function; Energy consumption; Generators; Hardware; Instruments; Mobile communication; Software; Mobile app; fine-grained energy estimation; program analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (ICSE), 2013 35th International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    978-1-4673-3073-2
  • Type

    conf

  • DOI
    10.1109/ICSE.2013.6606555
  • Filename
    6606555