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Issue No.09 - Sept. (2012 vol.11)
pp: 1441-1454
Xinyu Zhang , University of Michigan, Ann Arbor
Kang G. Shin , University of Michigan, Ann Arbor
WiFi interface is known to be 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 the 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 more than 60 percent of energy is consumed in IL, even with PSM enabled. To remedy this problem, we propose Energy-Minimizing idle Listening (E-MiLi) that reduces the power consumption in IL, given that the time spent in IL has already been optimized by sleep scheduling. Observing that radio power consumption decreases proportionally to its clock rate, E-MiLi adaptively downclocks 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, 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 downclocking 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 percent accuracy even with downclocking by a factor of 16. When integrated with 802.11, E-MiLi can reduce energy consumption by around 44 percent for 92 percent of users in real-world wireless networks.
Energy efficiency, IEEE 802.11 Standards, Power demand, Receivers, Software radio, Energy consumption, Switches, Synchronization, dynamic frequency scaling., Energy efficiency, CSMA wireless networks, idle listening, packet detection, adapting clock rate
Xinyu Zhang, Kang G. Shin, "E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks", IEEE Transactions on Mobile Computing, vol.11, no. 9, pp. 1441-1454, Sept. 2012, doi:10.1109/TMC.2012.112
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