[PAST EVENT] SAPSM: Smart Adaptive 802.11 PSM for Smartphones

September 7, 2012
3pm - 4pm
McGlothlin-Street Hall, Room 20
251 Jamestown Rd
Williamsburg, VA 23185Map this location
Effective WiFi power management can strongly impact the energy consumption on Smartphones. Through controlled experiments, we find that WiFi power management on a wide variety of Smartphones is a largely autonomous process that is processed completely at the driver level. Driver level implementations suffer from the limitation that important power management decisions can be made only by observing packets at the MAC layer. This approach has the unfortunate side effect that each application has equal opportunity to impact WiFi power management to consume more energy, since distinguishing between applications is not feasible at the MAC layer. The power cost difference between WiFi power modes is high (a factor of 20 times when idle), therefore determining which applications are permitted to impact WiFi power management is an important and relevant problem. In this paper we propose SAPSM: Smart Adaptive Power Save Mode. SAPSM labels each application with a priority with the assistance of a machine learning classifier. Only high priority applications affect the client's behavior to switch to CAM or Active mode, while low priority traffic is optimized for energy efficiency. Our implementation on an Android Smartphone improves energy savings by up to 56% under typical usage patterns.


Andrew worked for several start-up companies in Silicon Valley before deciding to return to school. He has been at William and Mary since 2009 where he has studied with Gang Zhou focusing on Smartphone energy conservation. He has published two papers in Ubicomp: both 2011 and 2012. He has a patent pending and plans to defend his dissertation this December.

Department of Computer Science