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Modeling Video Playback Power Consumption on Mobile Devices

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Published:15 April 2024Publication History

ABSTRACT

Advancements in mobile hardware and streaming technologies enable high-quality video streaming for mobile users, but this comes at a cost: a boost in power consumption. Despite detailed studies on power consumption during acquisition, existing studies fall short of considering recent technologies and, hence, of accurately capturing video playback power consumption. This paper presents a novel method to model mobile video playback power consumption. First, we identify the major components contributing to power consumption during video playback on mobile devices. Then, we develop models for each component to estimate their power consumption. Our experimental results show that our combined model estimates power consumption with 91% mean accuracy. Furthermore, our model maintains its high accuracy on an unseen device, achieving 88% mean accuracy despite the hardware and screen heterogeneity.

References

  1. 2020. DASH Industry Forum. https://dashif.org/Google ScholarGoogle Scholar
  2. 2020. Google ExoPlayer. https://github.com/google/ExoPlayerGoogle ScholarGoogle Scholar
  3. 2020. Monsoon High Voltage Power Monitor. Retrieved August 19, 2020 from https://www.msoon.com/online-store/High-Voltage-Power-Monitor-Part-Number-AAA10F-p90002590Google ScholarGoogle Scholar
  4. 2021. Test Media. Retrieved August 19, 2021 from https://media.xiph.org/Google ScholarGoogle Scholar
  5. 2023. Encoding For Streaming Sites. https://trac.ffmpeg.org/wiki/EncodingForStreamingSitesGoogle ScholarGoogle Scholar
  6. 2023. Ericsson Mobility Report, 2023. https://www.ericsson.com/49dd9d/assets/local/reports-papers/mobility-report/documents/2023/ericsson-mobility-report-june-2023.pdfGoogle ScholarGoogle Scholar
  7. 2023. iPhone 13 series battery life revealed. https://www.phonearena.com/news/apple-iphone-13-series-battery-capacities-leaked_id132514Google ScholarGoogle Scholar
  8. 2024. Glide Slider. https://github.com/firdausmaulan/GlideSliderGoogle ScholarGoogle Scholar
  9. 2024. OpenCV. https://docs.opencv.org/4.x/index.htmlGoogle ScholarGoogle Scholar
  10. Samira Afzal, Narges Mehran, Zoha Azimi Ourimi, Farzad Tashtarian, Hadi Amirpour, R.-C. Prodan, and Christian Timmerer. 2024. A Survey on Energy Consumption and Environmental Impact of Video Streaming. ArXiv abs/2401.09854 (2024). https://api.semanticscholar.org/CorpusID:267035135Google ScholarGoogle Scholar
  11. A. Anastasov. 2023. Galaxy S22 battery life & tests: upgrade or disappointment?Google ScholarGoogle Scholar
  12. Apple. 2023. Power and Battery.Google ScholarGoogle Scholar
  13. X. Chen, T. Tan, and G. Cao. 2019. Energy-Aware and Context-Aware Video Streaming on Smartphones. In 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). 861--870.Google ScholarGoogle Scholar
  14. P. Dash and C. Hu. 2021. How Much Battery Does Dark Mode Save? An Accurate OLED Display Power Profiler for Modern Smartphones. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys '21). Association for Computing Machinery, New York, NY, USA, 323--335. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Android Documentation. 2023. Battery Manager.Google ScholarGoogle Scholar
  16. C. Herglotz, S. Coulombe, C. Vazquez, A. Vakili, A. Kaup, and J. Grenier. 2020. Power Modeling for Video Streaming Applications on Mobile Devices. IEEE Access 8 (2020), 70234--70244.Google ScholarGoogle ScholarCross RefCross Ref
  17. M. Schuchhardt, S. Jha, R. Ayoub, M. Kishinevsky, and G. Memik. 2015. Optimizing Mobile Display Brightness by Leveraging Human Visual Perception. In Proceedings of the 2015 International Conference on Compilers, Architecture and Synthesis for Embedded Systems (Amsterdam, The Netherlands) (CASES '15). IEEE Press, 11--20.Google ScholarGoogle Scholar
  18. L. Sun, R. Sheshadri, W. Zheng, and D. Koutsonikolas. 2014. Modeling WiFi Active Power/Energy Consumption in Smartphones. In 2014 IEEE 34th International Conference on Distributed Computing Systems. 41--51. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. B. Turkkan, T. Dai, A. Raman, T. Kosar, C. Chen, M. Bulut, J. Zola, and D. Sow. 2022. GreenABR: Energy-Aware Adaptive Bitrate Streaming with Deep Reinforcement Learning. In Proceedings of the 13th ACM Multimedia Systems Conference (Athlone, Ireland) (MMSys '22). Association for Computing Machinery, New York, NY, USA, 150--163. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. C. Yue, S. Sen, B. Wang, Y. Qin, and F. Qian. 2020. Energy Considerations for ABR Video Streaming to Smartphones: Measurements, Models and Insights. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. L. Zou, A. Javed, and G. Muntean. 2017. Smart mobile device power consumption measurement for video streaming in wireless environments: WiFi vs. LTE. In 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). 1--6. Google ScholarGoogle ScholarCross RefCross Ref

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      • Published in

        cover image ACM Conferences
        GMSys '24: Proceedings of the Second International ACM Green Multimedia Systems Workshop
        April 2024
        33 pages
        ISBN:9798400706172
        DOI:10.1145/3652104

        Copyright © 2024 ACM

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        • Published: 15 April 2024

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