Dynamic Management of Power Consumption

  • Tajana Simunic
Part of the Series in Computer Science book series (SCS)


Power consumption of electronic devices has become a serious concern in the recent years. Power efficiency is necessary to lengthen the battery lifetime in the portable systems, as well as to reduce the operational costs and the environmental impact of stationary systems. Two new approaches that enable systems to save power by adapting to changes in environment are proposed: dynamic power management and dynamic voltage scaling. Dynamic power management (DPM) algorithms aim to reduce the power consumption at the system level by selectively placing components into low-power states. A new event-driven power management algorithm that guarantees globally optimal decisions is presented that is based on Time-Indexed Semi-Markov Decision Process model (TISMDP). TISMDP power management policies have been implemented on four devices: two different hard disks, a laptop WLAN card and a SmartBadge portable system [1]. The measurement results show power savings ranging from a factor of 1.7 up to 5.0 with performance basically unaffected. Dynamic voltage scaling (DVS) algorithms reduce energy consumption by changing processor speed and voltage at run-time depending on the needs of the applications running. This work extends the TISMDP power management model with a DVS algorithm, thus enabling even larger power savings. The measurements of MPEG video and MP3 audio algorithms running on the SmartBadge portable device show savings of a factor of three in energy consumption for combined DVS and DPM approaches.


Wireless Local Area Network Power Management Interarrival Time Sleep State Dynamic Voltage Scaling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Tajana Simunic
    • 1
  1. 1.HP LabsUSA

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