Title :
Modeling power consumption for video decoding on mobile platform and its application to power-rate constrained streaming
Author :
Xin Li ; Zhan Ma ; Fernandes, Felix C. A.
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Abstract :
This paper proposes an analytical power consumption model for H.264/AVC video decoding using hardware (HW) accelerator on popular mobile platforms. Our proposed model is expressed as the product of the power functions of video spatial resolution (i.e., frame size) and temporal resolution (i.e., frame rate). We have demonstrated that the same analytical model is applicable to different platforms. Model parameters are fixed for a specific platform. This indicates that HW accelerated video decoding is independent of the video content. Simulation results show the high accuracy for video decoding power prediction using proposed model, with the maximum relative prediction error less than 10%. Together with the video bit rate and perceptual quality models published in separated works, we propose to solve the power-rate optimized mobile video streaming problem, so as to maximum the video quality given the limited access network bandwidth and battery life for mobile devices.
Keywords :
decoding; image resolution; mobile computing; power consumption; prediction theory; video coding; video streaming; H.264-AVC video decoding; HW accelerator; hardware accelerator; limited access network bandwidth; maximum relative prediction error; mobile device battery life; mobile platform; perceptual quality models; power consumption; power functions; power-rate constrained streaming; power-rate optimized mobile video streaming problem; temporal resolution; video bit rate; video content; video decoding power prediction; video spatial resolution; Analytical models; Decoding; Mobile communication; Power demand; Power measurement; Spatial resolution; Streaming media; Power consumption modeling; power-rate optimization mobile platform; video decoding;
Conference_Titel :
Visual Communications and Image Processing (VCIP), 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-4405-0
Electronic_ISBN :
978-1-4673-4406-7
DOI :
10.1109/VCIP.2012.6410842