Rate: Power-Eicient Mobile Immersive Video Streaming

Smartphones have recently become a popular platform for deploying the computation-intensive virtual reality (VR) applications, such as immersive video streaming (a.k.a., 360-degree video streaming). One specic challenge involving the smartphone-based head mounted display (HMD) is to reduce the potentially huge power consumption caused by the immersive video. To address this challenge, we rst conduct an empirical power measurement study on a typical smartphone immersive streaming system, which identies the major power consumption sources. Then, we develop QuRate, a quality-aware and user-centric frame rate adaptation mechanism to tackle the power consumption issue in immersive video streaming. QuRate optimizes the immersive video power consumption by modeling the correlation between the perceivable video quality and the user behavior. Specically, QuRate builds on top of the user’s reduced level of concentration on the video frames during view switching and dynamically adjusts the frame rate without impacting the perceivable video quality. We evaluate QuRate with a comprehensive set of experiments involving 5 smartphones, 21 users, and 6 immersive videos using empirical user head movement traces. Our experimental results demonstrate that QuRate is capable of extending the smartphone battery life by up to 1.24X while maintaining the perceivable video quality during immersive video streaming. Also, we conduct an Institutional Review Board (IRB)approved subjective user study to further validate the minimum video quality impact caused by QuRate.

[1]  Eric Lo,et al.  Dash , 2020, Proceedings of the VLDB Endowment.

[2]  Nam Kim,et al.  Novel Therapeutic Game Controller for Telerehabilitation of Spastic Hands: Two Case Studies , 2019, 2019 International Conference on Virtual Rehabilitation (ICVR).

[3]  Rittwik Jana,et al.  Mobile VR on edge cloud: a latency-driven design , 2019, MMSys.

[4]  Ragnhild Eg,et al.  Playing with delay: an interactive VR demonstration , 2019, MMVE@MMSys.

[5]  Feng Qian,et al.  Flare: Practical Viewport-Adaptive 360-Degree Video Streaming for Mobile Devices , 2018, MobiCom.

[6]  Wei Gao,et al.  MUVR: Supporting Multi-User Mobile Virtual Reality with Resource Constrained Edge Cloud , 2018, 2018 IEEE/ACM Symposium on Edge Computing (SEC).

[7]  Wenyao Xu,et al.  Exploring Eye Adaptation in Head-Mounted Display for Energy Efficient Smartphone Virtual Reality , 2018, HotMobile.

[8]  Feng Qian,et al.  360° Innovations for Panoramic Video Streaming , 2017, HotNets.

[9]  Henri Toukomaa,et al.  Bandwidth Reduction of Omnidirectional Viewport-Dependent Video Streaming via Subjective Quality Assessment , 2017, AltMM@MM.

[10]  Gwendal Simon,et al.  360-Degree Video Head Movement Dataset , 2017, MMSys.

[11]  Nan Jiang,et al.  Power Evaluation of 360 VR Video Streaming on Head Mounted Display Devices , 2017, NOSSDAV.

[12]  Mehdi Bennis,et al.  Toward Interconnected Virtual Reality: Opportunities, Challenges, and Enablers , 2016, IEEE Communications Magazine.

[13]  Xin Liu,et al.  Viewing 360 degree videos: Motion prediction and bandwidth optimization , 2016, 2016 IEEE 24th International Conference on Network Protocols (ICNP).

[14]  Feng Qian,et al.  Optimizing 360 video delivery over cellular networks , 2016, ATC@MobiCom.

[15]  Songqing Chen,et al.  DASH2M: Exploring HTTP/2 for Internet Streaming to Mobile Devices , 2016, ACM Multimedia.

[16]  Mohammad Hosseini,et al.  Adaptive 360 VR Video Streaming: Divide and Conquer , 2016, 2016 IEEE International Symposium on Multimedia (ISM).

[17]  Minyi Guo,et al.  Profiling energy consumption of DASH video streaming over 4G LTE networks , 2016, MoVid '16.

[18]  Viswanathan Swaminathan,et al.  Power efficient mobile video streaming using HTTP/2 server push , 2015, 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP).

[19]  Guohong Cao,et al.  Energy-aware video streaming on smartphones , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[20]  Songqing Chen,et al.  Reducing display power consumption for real-time video calls on mobile devices , 2015, 2015 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[21]  Xin Li,et al.  Content-adaptive display power saving in internet mobile streaming , 2015, NOSSDAV.

[22]  Zhen Wang,et al.  Draining our glass: an energy and heat characterization of Google Glass , 2014, APSys.

[23]  D. Zee,et al.  Revisiting corrective saccades: Role of visual feedback , 2013, Vision Research.

[24]  Simon J. Julier,et al.  Design and implementation of an immersive virtual reality system based on a smartphone platform , 2013, 2013 IEEE Symposium on 3D User Interfaces (3DUI).

[25]  Yiran Chen,et al.  How is energy consumed in smartphone display applications? , 2013, HotMobile '13.

[26]  Kikuro Fukushima,et al.  Cognitive processes involved in smooth pursuit eye movements: behavioral evidence, neural substrate and clinical correlation , 2013, Front. Syst. Neurosci..

[27]  Eckehard G. Steinbach,et al.  A novel full-reference video quality metric and its application to wireless video transmission , 2011, 2011 18th IEEE International Conference on Image Processing.

[28]  Iraj Sodagar,et al.  The MPEG-DASH Standard for Multimedia Streaming Over the Internet , 2011, IEEE MultiMedia.

[29]  Mark T. Bolas,et al.  A design for a smartphone-based head mounted display , 2011, 2011 IEEE Virtual Reality Conference.

[30]  Lei Yang,et al.  Accurate online power estimation and automatic battery behavior based power model generation for smartphones , 2010, 2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

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

[32]  R. W. Jones.  International Telecommunication Union , 1950, International Organization.

[33]  Philippe Coiffet,et al.  Virtual Reality Technology , 2003, Presence: Teleoperators & Virtual Environments.

[34]  Irwin Sobel,et al.  An Isotropic 3×3 image gradient operator , 1990 .