Display power management policies in practice

  • Authors:
  • Stephen P. Tarzia;Peter A. Dinda;Robert P. Dick;Gokhan Memik

  • Affiliations:
  • Northwestern University, Evanston, IL, USA;Northwestern University, Evanston, IL, USA;University of Michigan, Ann Arbor, MI, USA;Northwestern University, Evanston, IL, USA

  • Venue:
  • Proceedings of the 7th international conference on Autonomic computing
  • Year:
  • 2010

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Abstract

We present the first study of the real-world behavior of display power management (DPM) policies. DPM policies control the mechanism of powering on and off the display - turning off the display typically reduces total system power by ~31%. The most widely used DPM policy, human interface device (HID) timeout, powers off the display after a user-configurable period of human interface device inactivity, and powers it back on in response to activity. To increase energy savings, we also consider an alternative policy, user presence detection, that uses sonar sensing to power off the display when user absence is detected. Our study captures how these DPM policies work "in the wild", both in terms of energy savings and the user irritation. We also determine the maximum energy saving opportunity for any DPM policy, based on measured behavior. Our study, based on a 3,738 hours of computer usage by 181 volunteers with different machines, reveals several surprising results. User idle periods follow power law distributions with little temporal correlation. The maximum possible reduction in energy used for the display is 81%, while the HID timeout policy manages to reduce this energy by 51%. Many users have already customized the HID timeout policy on their machines, resulting in a high variation of timeout values, and surprisingly low levels of user irritation. However, the 44% of users that have not customized HID timeouts experience more irritation. The proposed user presence detection policy, when effective, further reduces display energy consumption by 10% when combined with the HID timeout policy. 40% of the 2,869 machines tested can effectively generate and record ultrasound for sonar.