DE-BAR: Device Energy-Centric Backlight and Adaptive Region of Interest Mechanism for Wireless Mobile Devices

One of the main challenges in the smart-phone world is that they are battery constrained and the development of battery technologies have not kept pace with the required energy demand. In particular, there are still significant technological gaps on developing energy-aware solutions that would prolong the battery life of devices without affecting the quality of the distributed video/multimedia content. In this aspect, this paper proposes DE-BAR—a process based innovation that will provide a seamless battery saving mechanism, based on backlight and adaptive region of interest of the streamed multimedia content. This work intends to look at the nature of the video/multimedia content that is received in the device and adapts the energy consumption dynamically at three levels: Screen Colour, backlight and Intensity; and adaptive Region-of-Interest (RoI) based variation in the multimedia content. Notably, the work provides the mechanism for real-time adaptation. The colour intensity, number of RoI for the video sequence and the frame rate is decided by the spatial and temporal complexity of the video. The energy consumption is measured using an Arduino board while video quality is analyzed using extensive subjective tests. The results indicate that more than 50% energy could be saved in the device while retaining above average perceptual video quality.

[1]  Lester C. Loschky,et al.  Reduced saliency of peripheral targets in gaze-contingent multi-resolutional displays: blended versus sharp boundary windows , 2002, ETRA.

[2]  Cristina Hava Muntean,et al.  Quality Utility modelling for multimedia applications for Android Mobile devices , 2012, IEEE international Symposium on Broadband Multimedia Systems and Broadcasting.

[3]  Gabriel-Miro Muntean,et al.  EDAS– Energy-Efficient Device-based Adaptive Cross-Layer Scheme for Wireless Multimedia Transmission , 2015 .

[4]  Hrishikesh Venkataraman,et al.  Analysis of region of interest (RoI) of multimedia content using eye-tracker: poster , 2016, MobiHoc.

[5]  Jahon Koo,et al.  Adaptive channel control scheme to reduce channel zapping time of mobile IPTV service , 2011, IEEE Transactions on Consumer Electronics.

[6]  Chuck Yoo,et al.  Scalable ROI algorithm for H.264/SVC-based video streaming , 2011, 2011 IEEE International Conference on Consumer Electronics (ICCE).

[7]  Benjamin Watson,et al.  Managing level of detail through peripheral degradation: effects on search performance with a head-mounted display , 1997, TCHI.

[8]  Gabriel-Miro Muntean,et al.  Energy consumption analysis of video streaming to Android mobile devices , 2012, 2012 IEEE Network Operations and Management Symposium.

[9]  Gabriel-Miro Muntean,et al.  Adaptive Energy Optimization in Multimedia-Centric Wireless Devices: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[10]  Gabriel-Miro Muntean,et al.  Battery and Stream-Aware Adaptive Multimedia Delivery for wireless devices , 2010, IEEE Local Computer Network Conference.

[11]  Gabriel-Miro Muntean,et al.  Subjective Assessment of Region of Interest-Aware Adaptive Multimedia Streaming Quality , 2009, IEEE Transactions on Broadcasting.

[12]  Gernot Heiser,et al.  An Analysis of Power Consumption in a Smartphone , 2010, USENIX Annual Technical Conference.