Energy Efficient WiFi Display

Dec 30, 2015  |  2:00pm | ESB 1001
Xinyu Zhang, University of Wisconsin, Madison
Assistant Professor of Electrical and Computer Engineering, University of Wisconsin, Madison

WiFi Display, also called Miracast, is an emerging technology that allows a mobile device (source) to duplicate its screen content to an external display (sink) via a peer-to-peer WiFi link. Despite its growing popularity and diverse application scenarios, Miracast involves a host of power hungry operations like video encoding/decoding and WiFi, which can quickly drain off a mobile device’s battery. In this talk, I will introduce our recent study on the energy efficiency issue in Miracast.  We started with in-depth measurement experiments to quantify and model key parameters that scale Miracast’s power consumption. With the measurement observations, we designed a set of optimization mechanisms to bypass redundant codec operations, reduce video tail traffic, and relocate the Miracast channel dynamically to maximize transmission efficiency. This optimized Miracast framework has been implemented on an Android smartphone. Experimental results show that the legacy Miracast system costs 1.3 to 2.4 Watts. Our framework reduces the power consumption by 29% to 61%, depending on the Miracast application’s video traffic patterns.  Our experiments also point to other potential issues in Miracast, such as long setup latency and response time.


Xinyu Zhang is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. He received the B.E. degree in 2005 from Harbin Institute of Technology, the M.S. degree in 2007 from the University of Toronto, and the Ph.D. degree in 2012 from the University of Michigan. He worked as a research intern at Microsoft Research Asia from May to Aug. 2010, and at NEC Labs American from May to Dec. 2011. His research interest lies in designing cross-layer protocols that improve wireless network performance, as well as mobile applications that enable fine-grained context sensing. His work spans the areas of wireless networking, communications engineering and mobile computing, involving both mathematical analysis and system implementation. He received ACM MobiCom Best Paper Award in 2011, and NSF CAREER award in 2014.

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