• DocumentCode
    122494
  • Title

    PowerPi: Measuring and modeling the power consumption of the Raspberry Pi

  • Author

    Kaup, Fabian ; Gottschling, Philip ; Hausheer, David

  • Author_Institution
    Peer-to-Peer Syst. Eng. Group, Tech. Univ. Darmstadt, Darmstadt, Germany
  • fYear
    2014
  • fDate
    8-11 Sept. 2014
  • Firstpage
    236
  • Lastpage
    243
  • Abstract
    An increasing number of households is connected to the Internet via DSL or cable, for which home gateways are required. The optimization of these - caused by their large number - is a promising area for energy efficiency improvements. Since no power models for home gateways are currently available, the optimization of their power state is not possible. This paper presents PowerPi, a power consumption model for the Raspberry Pi which is used as a substitute to conventional home gateways to derive the impact of typical hardware components on the energy consumption. The different power states of the platform are measured and a power model is derived, allowing to estimate the power consumption based on CPU and network utilization only. The proposed power model estimates the power consumption resulting in a RMSE of less than 3.3%, which is slightly larger than the maximum error of the measurements of 2.5%.
  • Keywords
    Internet; energy conservation; home networks; internetworking; low-power electronics; microcomputers; power aware computing; CPU; DSL; Internet; PowerPi; Raspberry Pi; cable; energy consumption; energy efficiency improvements; home gateways; network utilization; power consumption measurement; power consumption modeling; power state optimization; Bandwidth; Current measurement; Monitoring; Power demand; Power measurement; Software measurement; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Local Computer Networks (LCN), 2014 IEEE 39th Conference on
  • Conference_Location
    Edmonton, AB
  • Print_ISBN
    978-1-4799-3778-3
  • Type

    conf

  • DOI
    10.1109/LCN.2014.6925777
  • Filename
    6925777