한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제20권1호
  • /
  • Pages.1-9
  • /
  • 2017
  • /
  • 1229-7771(pISSN)
  • /
  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
권호 표지
DOI QR코드

DOI QR Code

무선망 특성을 고려한 효율적 비디오 스트리밍 재생률 선택 기술

An Efficient Mobile Video Streaming Rate Selection Technique based on Wireless Network Characteristics

  • Pak, Suehee (Dept. of Computer Science, Dongduk Women's University)
  • 투고 : 2016.09.12
  • 심사 : 2016.10.17
  • 발행 : 2017.01.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Explosive deployment of smart mobile devices such as smart phones, and tablets along with expansion of wireless internet bandwidth have enabled the deployment of mobile video streaming such that video traffic becomes the most important service in wireless networks. Recently, for more efficient video streaming services, the ISO MPEG group standardized a protocol called DASH (Dynamic Adaptive Streaming over HTTP) and the standard has been quickly adopted by many service providers such as YouTube and Netflix. Despite of the convenience of mobile streaming services, users also suffer from low QoE(Quality of Experience) due to dynamic channel fluctuations and unnecessary downloading due to high churning rates. This paper proposes a noble efficient video rate selection algorithm considering user buffer level, channel condition and churning rate. Computer simulation based performance study showed that the proposed algorithm improved the QoE significantly compared to a method that determines the video rate based on current channel conditions. Especially, the proposed method reduced the rebuffering rate, one of the most important performance factors of the QoE, to a nonnegligible level.

키워드

참고문헌

  1. Cisco VNI White Paper, http://www.cisco.com/c/en/us/solutions/collateral/serviceprovider/visual-networking-index-vni/complete- white-paper-c11-481360.html, June, 2016.
  2. T.C. Thang, Q.D. Ho, J.W. Kang, and A.T. Pham, "Adaptive Streaming of Audiovisual Content Using MPEG DASH," IEEE Transaction on Consumer Electronics, Vol. 58, No. 1, pp. 78-85, 2012. https://doi.org/10.1109/TCE.2012.6170058
  3. M.A. Hoque, M. Siekkinen, and J.K. Nurminen, "Using Crowd-sourced Viewing Statistics to Save Energy in Wireless Video Streaming," Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, pp. 377-388, 2013.
  4. M. Ghobadi, Y. Cheng, A. Jain, and M. Mathis, "Trickle: Rate Limiting YouTube Video Streaming," Proceeding of Usenix Annual Technical Conference, pp. 6-15, 2012.
  5. L.D. Cicco, V. Caldaralo, and V. Palmisano, "Elastic: A Client-side Controller for Dynamic Adaptive Streaming over http (Dash)," Proceeding of 20th International Packet Video Workshop, pp. 1-8, 2013.
  6. J. Jiang, V. Sekar, and H. Zhang, "Improving Fairness, Efficiency, and Stability in httpbased Adaptive Video Streaming with Festive," Proceedings of the 8th International Conference on Emerging Networking Experiments and Technologies, pp. 97-108, 2012.
  7. T. Huang, R. Johari, N. McKeown, M. Trunnell, and M. Watson, "A Buffer-based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service," Proceedings of the 2014 ACM Conference on SIGCOMM, pp. 187-198, 2014.
  8. W. Hu and G. Cao, "Energy-aware Video Streaming on Smartphones," Proceedings of the 34th IEEE International Conference on Computer Communications, pp. 1185-1193, 2015.
  9. J. Chen, R. Mahindra, M. A. Khojastepour, S. Rangarajan, and M. Chiang, "A Scheduling Framework for Adaptive Video Delivery over Cellular Networks," Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, pp. 389-400, 2013.
  10. G. Tian and Y. Liu, "Towards Agile and Smooth Video Adaptation in Dynamic HTTP Streaming," Proceedings of the 8th International Conference on Emerging Networking Experiments and Technologies, pp. 109-120, 2012.
  11. S. Akhshabi, L. Anantakrishnan, A.C. Begen, and C. Dovrolis, "What Happens When HTTP Adaptive Streaming Players Compete for Bandwidth?," Proceedings of the 22nd International Workshop on Network and Operating System Support for Digital Audio and Video, pp. 9-14, 2012.
  12. S. Akhshabi, S. Narayanaswamy, A.C. Begen, and C. Dovrolis, "An Experimental Evaluation of Rate-adaptive Video Players over HTTP," Signal Processing: Image Communication, Vol. 27, No. 4, pp. 271-287, 2012. https://doi.org/10.1016/j.image.2011.10.003
  13. X. Yin, A. Jindal, V. Sekar, and B. Sinopoli, "A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP," Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, pp. 325-338, 2015.
  14. X. Xie, X. Zhang, S. Kumar, and L. Li, "piStream: Physical Layer Informed Adaptive Video Streaming over LTE," Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, pp. 413-425, 2015.
  15. J. Kim,"Mobile Client Buffer Level-based Scheduling Algorithms for Variable-Bit-Rate Video Stream Transmission," Journal of Korea Multimedia Society, Vol. 15, No. 6, pp. 814-826, 2012. https://doi.org/10.9717/kmms.2012.15.6.814