A User Driven Adaptive Bandwidth Video Streaming System

사용자 기반 가변 대역폭 영상 스트리밍 시스템

  • Received : 2014.12.30
  • Accepted : 2015.03.12
  • Published : 2015.04.30


Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.


Multimedia Communication;Cognitive Computing;Bandwidth Adaptation;Machine Learning;User Preference


  1. O. Oyman, S. Singh, Quality of experience for http adaptive streaming services, IEEE Communications Magazine 50 (4) (2012) 20-27.
  2. H. Schulzrinne, Real time streaming protocol (rtsp).
  3. Http live streaming overview, Apple Inc.Available from:
  4. A. Zambelli, Iis smooth streaming technical overview, Microsoft Corporation.
  5. V. K. Adhikari, Y. Guo, F. Hao, M. Varvello, V. Hilt, M. Steiner, Z.-L. Zhang, Unreeling netflix: Understanding and improving multi-cdn movie delivery, in: 2012 Proceedings IEEE INFOCOM, IEEE, 2012, pp. 1620-1628.
  6. L. De Cicco, S. Mascolo, V. Palmisano, Feedback control for adaptive live video streaming, in: Proceedings of the second annual ACM conference on Multimedia systems, ACM, 2011, pp. 145-156.
  7. J.-R. Ohm, Advances in scalable video coding, Proceedings of the IEEE 93 (1) (2005) 42-56.
  8. H. Schwarz, D. Marpe, T. Wiegand, Overview of the scalable video coding extension of the h. 264/avc standard, IEEE Transactions on Circuits and Systems for Video Technology 17 (9) (2007) 1103-1120.
  9. I. Unane, I. Urteaga, R. Husemann, J. Del Ser, V. Roseler, A. Rodriguez, P. Sanchez, A tutorial on h.264/svc scalable video coding and its tradeoff between quality, coding, effi ciency, and performance, in: J. D. S. Lorente (Ed.), Recent Advances on Video Coding, InTech, 2011, available from:
  10. T. Lohmar, T. Einarsson, P. Frojdh, F. Gabin, M. Kampmann, Dynamic adaptive http streaming of live content, in: 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), IEEE, 2011, pp. 1-8.
  11. T. Wiegand, G. J. Sullivan, G. Bjontegaard, A. Luthra, Overview of the h. 264/avc video coding standard, IEEE Transactions on Circuits and Systems for Video Technology 13 (7) (2003) 560-576.
  12. S. Wenger, T. Stockhammer, Rtp payload format for h. 264 video.
  13. S. Wenger, H. 264/avc over ip, IEEE Transactions on Circuits and Systems for Video Technology 13 (7) (2003) 645-656.
  14. T.Stockhammer, M.M.Hannuksela, T.Wiegand, H.264/AVC in wireless environments, IEEE Transactions on Circuits and Systems for Video Technology 13 (7) (2003) 657-673.
  15. H. ITU-T RECOMMENDATION, 264 advanced video coding for generic audio visual services, ISO/IEC 14496.
  16. Y. Ozturk, M. Kulkarni, DiChirp: direct injection bandwidth estimation, International Journal of Network Management 18 (5) (2008) 377- 394. doi:10.1002/nem.674. URL
  17. C.-C. Chang, C.-J. Lin, Libsvm: a library for support vector machines, ACM Transactions on Intelligent Systems and Technology (TIST) 2 (3) (2011) 27.


Supported by : 원광대학교