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Battery-aware rate adaptation for extending video streaming playback time

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Abstract

Multimedia streaming applications are computation and network intensive that put a high demand on battery usage of mobile devices. Battery usage forms an important metric in user satisfaction, as increased battery consumption results in faster battery depletion and eventually leads to battery outage. In this paper, we propose an adaptation technique, referred as Battery-Aware Rate Adaptation (BARA) scheme, which adapts to the appropriate bit rate to prolong the battery lifetime. BARA considers both the wireless channel conditions, as well as the device’s battery level, to determine the best transmission rate for optimizing the mobile battery consumption. Actual experiment and simulation results corroborate that compared to the conventional techniques, BARA can save more than 40% of battery power, while extending the video playback time by 20%.

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  1. http://www.w3.org/TR/2005/REC-SMIL2-20050107/

References

  1. Ahmad H, Saxena N, Roy A, De P (2016) Extending video playback time with limited residual battery. IEEE Commun Lett 20(8):1659–1662

    Article  Google Scholar 

  2. Akamai Technologies Inc. (2012) Encoding Best Practices for Akamai HD for iPhone and iPad. Akamai HD Network: White Paper

  3. Akamai Play version 2.0 (2016) [Android Application Software], Octoshape Aps

  4. Akamai Technologies (2017) CDN Learning Center. https://www.akamai.com/uk/en/cdn/. Accessed 5 Dec. 2017

  5. Alsheikh M A, Hoang D T, Niyato D, Tan H P, Lin S (2015) Markov decision processes with applications in wireless sensor networks: a survey. IEEE Comm Surv Tutorials 17(3):1239–1267

    Article  Google Scholar 

  6. BBC News (2014) Jimmy Page: How Stairway to Heaven was Written - BBC News. https://www.youtube.com/watch?v=DDo4CA13LbY. Accessed 9 Jan. 2016

  7. Biermann VK (2011) Data Protection: Betrayed by our own data. http://www.zeit.de/digital/datenschutz/2011-03/data-protection-malte-spitz. Accessed 10 Jan. 2016

  8. Blender Foundation (2008) Big Buck Bunny. http://www.bigbuckbunny.org/. Accessed 9 Jan. 2016

  9. Blender Foundation (2012) Tears of Steel - Blender VFX Open Movie. https://www.youtube.com/watch?v=R6MlUcmOul8&list=PL6B3937A5D230E335&index=6. Accessed 9 Jan. 2016

  10. Bokani A, Hassan M, Kanhere S S, Zhu X (2015) Optimizing HTTP-based adaptive streaming in vehicular environment using markov decision process. IEEE Trans Multimed 17(12):2297–2309

    Article  Google Scholar 

  11. Bui D H, Lee K, Oh S, Shin I, Shin H, Woo H, Ban D (2013) Greenbag: Energy-efficient bandwidth aggregation for real-time streaming in heterogeneous mobile wireless networks. In: IEEE Real-Time Systems Symposium (RTSS), pp 57–67

  12. Cao Y, Jiang T, Chen X, Zhang J (2016) Social-aware video multicast based on device-to-device communications. IEEE Trans Mob Comput 15(6):1528–1539

    Article  Google Scholar 

  13. Cicco L D, Mascolo S, Palmisano V (2011) Feedback Control for Adaptive Live Video Streaming. In: ACM Conference on Multimedia Systems, pp 145–156

  14. Cisco (2016) Cisco Visual Networking Index: Forecast and Methodology, 2015-2020 White Paper. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html. Accessed 13 Oct. 2016

  15. Claeys M, Latre S, Famaey J, Wu T, Leekwijck W V, Turck F D (2013) Design of a Q-learning-based client quality selection algorithm for http adaptive video streaming. In: Adaptive and Learning Agents Workshop, part of AAMAS2013 (ALA-2013), pp 30–37

  16. Ding R, Muntean G M (2013) Device characteristics-based differentiated energy-efficient adaptive solution for video delivery over heterogeneous wireless networks. In: Proceedings of the IEEE Wireless Commission and Networking Conference, pp 4588–4593

  17. Dinh H T, Lee C, Niyato D, Wang P (2013) A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Comm Mob Comput 13(8):1587–1611

    Article  Google Scholar 

  18. Ejembi O, Bhatti S N (2014) Help save the planet: please do adjust your picture. In: ACM Proceedings of the ACM International Conference on on Multimedia, pp 427–436

  19. Farahbakhsh R, Cuevas A, Ortiz A M, Han X, Crespi N (2015) How far is facebook from me? facebook network infrastructure analysis. IEEE Comm Mag 53 (9):134–142

    Article  Google Scholar 

  20. Grant AE, Meadows JH (2006) Communication Tech. Update, 10th edn. Focal Press, Boston, pp 126–127

    Google Scholar 

  21. Guruprasad R, Dev S (2015) Battery aware video delivery techniques using rate adaptation and base station reconfiguration. IEEE Trans Multimed 17(9):1630–1645

    Article  Google Scholar 

  22. Hoque M A, Siekkinen M, Nurminen J K (2014) Energy efficient multimedia streaming to mobile devices - a survey. IEEE Commun Surv Tutorials 16(1):579–597

    Article  Google Scholar 

  23. Hu W, Cao G (2015) Energy-aware video streaming on smartphones. In: IEEE International Conference on Computer Commission, pp 1185–1193

  24. Kennedy M, Ventakaraman H, Muntean G M (2010) Battery and stream-aware adaptive multimedia delivery for wireless devices. In: IEEE 35th Conference on Local Computer Networks (LCN), pp 843–846

  25. ICON Motosports (2012) Motorcycle vs. Car Drift Battle 2. https://www.youtube.com/watch?v=Te0V71sGoxA. Accessed 9 Jan. 2016

  26. ITU-T Rec. P.862.1 (2003) Mapping Function for Transforming P.862 Raw Result Scores to MOS-LQO

  27. Khan S, Schroeder D, El Essaili A, Steinbach E (2014) Energy-efficient and QoE-driven Adaptive HTTP Streaming over LTE. In: IEEE Wireless Commission and Networking Conference on Mobile and Wireless Networks, pp 2354–2359

  28. Lauridsen M, Noel L, Sorensen T B, Mogensen P (2014) An empirical LTE smartphone power model with a view to energy efficiency evolution. Intel Tech J 18(1):172–193

    Google Scholar 

  29. Lee H, Lee Y, Lee J, Lee D, Shin H (2009) Design of a mobile video streaming system using adaptive spatial resolution control. IEEE Trans Consum Electron 5(3):1682–1689

    Article  Google Scholar 

  30. Li Y, Markopoulou A, Apostolopoulos J, Bambos N (2008) Content-aware playout and packet scheduling for video streaming over wireless links. IEEE Trans Multimed 10(5):885–895

    Article  Google Scholar 

  31. Li X, Dong M, Ma Z, Fernandes F C (2012) GreenTube: Power Optimization for Mobile Video Streaming via Dynamic Cache Management. In: Proceedings of the 20th. ACM International Conference on Multimedia, pp 279–288

  32. Liberal F, Taboada I, Fajardo J O (2013) Dealing with energy-QoE trade-offs in mobile video. J Comput Netw Comm 2013:1–12

    Article  Google Scholar 

  33. Mkwawa I, Lingfen S (2013) Battery voltage discharge rate prediction and video content adaptation in mobile devices over 3G access networks. J ZTE Commun 11 (1):44–50

    Google Scholar 

  34. Penttinen J T J (2016) LTE-A radio network. In: The LTE-Advanced Deployment Handbook: The Planning Guidelines for the Fourth Generation Networks. 1st edn. Wiley, UK, pp 131–133

  35. PowerTutor (2013) [Open Source Application Software], PowerTutor.org

  36. Ronen A (2014) Akamai Expands CDN to the RAN with Saguna. http://broabandtrafficmanagement.blogspot.kr/2014/09/akamai-expands-cdn-to-ran-with-saguna.html. Accessed 9 Jan. 2016

  37. Roy A, De P, Saxena N (2015) Location-based social video sharing over next generation cellular networks. IEEE Comm Magaz 53(10):136–143

    Article  Google Scholar 

  38. Saw L H, Somasundaram K, Ye Y, Tay A A O (2014) Electro-thermal analysis of lithium iron phosphate battery for electric vehicles. J Power Sources 249:231–238

    Article  Google Scholar 

  39. Saxena N, Roy A (2015) Exploiting Multicast in LTE Networks for Smart Grids Demand Response. In: IEEE International Conference on Commission (ICC), pp 3155–3160

  40. Spitz M (2011) CRAWDAD dataset spitz/cellular (v. 2011-05-04). http://crawdad.org/spitz/cellular/20110504. Accessed 10 Jan. 2016

  41. Sun Y, Yin X, Jiang J, Sekar V, Lin F, Wang N, Liu T, Sinopoli B (2016) CS2P: Improving video bitrate selection and adaptation with data-driven throughput prediction. In: Proceedings of the 2016 ACM Special Interest Group on Data Commission (SIGCOMM) Conference, pp 272–285

  42. Transformers 4 - Optimus vs. Lockdown (2014) https://www.youtube.com/watch?v=LMMP4ILcalI. Accessed 9 Jan. 2016

  43. Wang X, Chen M, Kwon T T, Yang L T, Leung V C M (2013) AMES-cloud: A framework of adaptive mobile video streaming and efficient social video sharing in the clouds. IEEE Trans Multimed 15(4):811–820

    Article  Google Scholar 

  44. Xing M, Xiang S, Cai L (2014) A real-time adaptive algorithm for video streaming over multiple wireless access networks. IEEE J Sel Areas Comm 32(4):795–805

    Article  Google Scholar 

  45. Yan Z, Chen C W (2016) RnB: Rate and brightness adaptation for rate-distortion-energy tradeoff in HTTP adaptive streaming over mobile devices. In: Proceedings of the 22nd. ACM International Conference on Mobile Computing and Networking (MobiCom), pp 308–319

  46. Yin X, Jindal A, Sekar V, Sinopoli B (2015) A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP. ACM SIGCOMM Comput Comm Rev 45(4):325–338

    Article  Google Scholar 

  47. Zhou C, Lin CW, Guo Z (2016) mDASH: A markov decision-based rate adaptation approach for dynamic HTTP streaming. IEEE Trans Multimed 18(4):738–751

    Article  Google Scholar 

  48. Zhu H, Cao Y, Wang W, Liu B, Jiang T (2015) QoE-aware resource allocation for adaptive device-to-device video streaming. IEEE Netw 29(6):6–12

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF− 2016R1D1A1B03935633).

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Correspondence to Navrati Saxena.

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Ahmad, H., Saxena, N., Roy, A. et al. Battery-aware rate adaptation for extending video streaming playback time. Multimed Tools Appl 77, 23877–23908 (2018). https://doi.org/10.1007/s11042-017-5603-z

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