Kang G. Shin, E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks (February 3, 2012)
Channel: securitylectures
Date: 26/08/2012

From the CISR video library (http://www.cisr.us)

Dr. Kang G. Shin, University of Michigan
E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks
February 3, 2012

at the
Naval Postgraduate School
(http://www.nps.edu)

ABSTRACT
The WiFi interface is a primary energy consumer in mobile devices, and idle listening (IL) is the dominant source of energy consumption in WiFi. Most existing protocols, such as 802.11 power-saving mode (PSM), attempt to reduce the time spent in IL by sleep scheduling. However, through an extensive analysis of real-world traffic, we found that more than 60% of energy is consumed in IL, even with PSM enabled. To remedy this problem, we propose E-MiLi (Energy-Minimizing idle Listening), which reduces the power consumption in IL, given that the time spent in IL has already been optimized by sleep scheduling. Since radio power consumption decreases proportionally to its clock-rate, E-MiLi adaptively down-clocks the radio during IL, and reverts to full clock-rate when an incoming packet is detected or a packet has to be transmitted. E-MiLi incorporates sampling rate invariant detection (SRID), ensuring accurate packet detection and address filtering even when the receiver's sampling clock-rate is much lower than the signal bandwidth. Further, it employs an opportunistic down-clocking mechanism to optimize the efficiency of switching clock-rate, based on a simple interface to existing MAC-layer scheduling protocols. We have implemented E-MiLi on the USRP software radio platform. Our experimental evaluation shows that E-MiLi can detect packets with close to 100% accuracy even with down-clocking by a factor of 16. When integrated with 802.11, E-MiLi can reduce energy consumption by around 44% for 92% of users in realworld wireless networks. Joint work with Xinyu Zhang presented at ACM MobiCom'11.

About Dr. Kang G. Shin 

Dr. Kang G. Shin is the Kevin & Nancy O'Connor Professor of Computer Science in the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. His current research focuses on computing systems and networks as well as on embedded real-time and cyber-physical systems, all with emphasis on timeliness, security, and dependability.