• DocumentCode
    2624872
  • Title

    Intelligent power saving technique for mobile devices

  • Author

    Mora, Jaime ; Leu, Jenq-Shiou

  • Author_Institution
    Dept. of Electron. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
  • fYear
    2012
  • fDate
    15-17 Oct. 2012
  • Firstpage
    504
  • Lastpage
    508
  • Abstract
    Power saving in mobile devices has become a hot topic nowadays. Enhancing user experience through intelligent techniques that help to extend battery lifetime is today´s goal for many manufacturers and developers. Different approaches to improve power consumption have focused on improving the hardware used, the operating system, and/or the applications performance; however, this study´s focusisto design an intelligent software framework. After a throughout evaluation of the power consumption in different modules of the phone, in order to identify which modules consume power the most,a reinforcement learning method is proposed to effectively deal with this issue by granting/denying accessto the user of executing battery-draining tasks.
  • Keywords
    learning (artificial intelligence); mobile handsets; power consumption; telecommunication computing; telecommunication power supplies; battery lifetime; battery-draining tasks; intelligent power saving technique; intelligent software framework; mobile devices; operating system; power consumption; reinforcement learning method; Batteries; IEEE 802.11 Standards; Learning; Power demand; Power measurement; Smart phones; Android; Markov Decision Process; Smartphones; power saving techniques; reinforcement learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (APCC), 2012 18th Asia-Pacific Conference on
  • Conference_Location
    Jeju Island
  • Print_ISBN
    978-1-4673-4726-6
  • Electronic_ISBN
    978-1-4673-4727-3
  • Type

    conf

  • DOI
    10.1109/APCC.2012.6388189
  • Filename
    6388189