DOI QR코드

DOI QR Code

Adaptive Multi-level Streaming Service using Fuzzy Similarity in Wireless Mobile Networks

무선 모바일 네트워크상에서 퍼지 유사도를 이용한 적응형 멀티-레벨 스트리밍 서비스

  • Lee, Chong-Deuk (Div. of Electronic Engineering, Chonbuk National University)
  • 이종득 (전북대학교 전자 공학부)
  • Received : 2010.06.10
  • Accepted : 2010.09.08
  • Published : 2010.09.30

Abstract

Streaming service in the wireless mobile network environment has been a very challenging issue due to the dynamic uncertain nature of the channels. Overhead such as congestion, latency, and jitter lead to the problem of performance degradation of an adaptive multi-streaming service. This paper proposes a AMSS (Adaptive Multi-level Streaming Service) mechanism to reduce the performance degradation due to overhead such as variable network bandwidth, mobility and limited resources of the wireless mobile network. The proposed AMSS optimizes streaming services by: 1) use of fuzzy similarity metric, 2) minimization of packet loss due to buffer overflow and resource waste, and 3) minimization of packet loss due to congestion and delay. The simulation result shows that the proposed method has better performance in congestion control and packet loss ratio than the other existing methods of TCP-based method, UDP-based method and VBM-based method. The proposed method showed improvement of 10% in congestion control ratio and 8% in packet loss ratio compared with VBM-based method which is one of the best method.

무선 모바일 네트워크 환경에서 스트리밍 서비스는 불확실한 동적 채널 속성으로 인하여 매우 중요한 이슈가 되고 있다. 특히 혼잡, 지연, 지터 등과 같은 오버헤드는 적응형 멀티-레벨 스트리밍 서비스의 성능 저하를 가져오고 있다. 본 논문에서는 무선 모바일 네트워크상에서의 가변 대역폭, 이동성 자원 제약 등으로 인한 성능 저하를 줄이기 위하여 AMSS 메카니즘을 제안한다. 제안된 AMSS는 다음과 같은 목적을 두고서 스트리밍 서비스를 최적화하는데 있다. 1) 퍼지 유사도 척도 이용, 2) 버퍼 오버플로우와 자원 소모로 인한 패킷 손실 최소화, 3) 혼잡과 지연으로 인한 패킷 손실 최소화. 시뮬레이션 결과 제안된 기법이 기존의 TCP-기반 기법, UDP-기반 기법, 그리고 VBM-기반 기법에 비해서 혼잡 제어와 패킷 손실율의 성능이 더 우수함을 보인다. 제안된 기법은 성능이 우수한 VBM-기반 기법과 비교해 볼 때 혼잡 제어율은 10%, 그리고 패킷 손실율은 8%의 성능 향상을 보였다.

Keywords

References

  1. C. Huitema, "Real-Time Control Protocol(RTCP) attribute in session Description Protocol(SDP)," IETF, RFC 3605, October, 2003.
  2. Audio-Video Transport Working Group, H. Schulzrinne, S. Casner, R. Frederick and V. Jacobsom, "RTP: A Transport Protocol for Real-Time Applications," IETF, RFC 1889, January 1996.
  3. A. Bulut and A. K. Singh, "Swat: Hierarchical Stream Summerization in Large Network," Proc. Int'l Conf. pp. 303-314. 2003.
  4. J. Jung, B. Krishnamurthy, and M. Rabinovich, "Flash Crowds and Denial of Service Attacks: Characterization and Implications for CDN's and WEb sites," in Proc, Int'l www Conf. 2002.
  5. C. Charu. A. J. Han, J. Wang, and S. Y. Phillips, "A Framework for Demand Classification of Evolving Data Streams," IEEE Trans. on Knowledge and Data Eng., vol. 18, no. 5, pp. 577-589, 2006. https://doi.org/10.1109/TKDE.2006.69
  6. Z. Xiang, Q. Zhang, W. Zhu, and Y. Q. Zhang, "Peer-to-Peer Based Multimedia Distribution Services," IEEE Trans. on Multimedia, vol. 6, no. 2, pp.343-354, 2004. https://doi.org/10.1109/TMM.2003.822819
  7. B. Xie and W. Zeng, "Rate Distortion Optimized Dynamic Bitstream Switching for Scalable Video Streaming", In Proc. IEEE Int. Conf, Multimedia and Expo, Taipei, Taiwan, Jun, 2004.
  8. J. Widmer, R. Denda, and M. Murve, "A Survey on TCP-friendly Congestion Control", IEEE Network, vol. 15, no. 3, pp. 28-37, 2001. https://doi.org/10.1109/65.923938
  9. L. Cai, X. Shen, J. Pan, and J. W. Mark, "Performance Analysis of TCP-friendly AIMD Algorithms for Multimedia Apllications", IEEE Trans. Multimedia, Vol. 7, No. 2, pp. 339-355, 2005. https://doi.org/10.1109/TMM.2005.843360
  10. N. R. Sastry and S. S. Lam, "CYRF : A Theory og Window-Based Uni-cast Congestion Control", IEEE/ACM Trans. Network, Vol. 13, N0. 2, pp. 330-342, 2005. https://doi.org/10.1109/TNET.2005.845545
  11. M. Handly, S. Floyd, J. Padhye, and J. Widmer, "TCP-friendly Rate Control : Protocol Specification", in IETF RFC 3448, 2003.
  12. S. Sen, J. L. Rexford, J. K. Dey, J. F. Kurose, and D. F. Towsley, "On-line Smoothing of Variable B-t-Rate Streaming Video", IEEE Trans. Multimedia, Vol. 2, No. 1, pp. 37-48, 2000. https://doi.org/10.1109/6046.825793
  13. T. Kim and M. H. Ammar, "Optimal Quality Adaptation for Scalable Encoded Video", IEEE J. Sel. Areas Commu, Vol. 23, No. 2, pp. 344-356, 2005. https://doi.org/10.1109/JSAC.2004.839390
  14. K. Atanassov, "Intuitionistic Fuzzy Sets," Fuzzy Sets Syst., vol.20, pp.87-96, 1986. https://doi.org/10.1016/S0165-0114(86)80034-3
  15. P. Zhu, W. Zeng, and C. Li, "Joint Design of Source Rate Control and QoS-Aware Congestion Control for Video Streaming Over the Internet," IEEE Trans. on Multimedia, vol. 9, no.2, pp.366-376, 2007. https://doi.org/10.1109/TMM.2006.886284
  16. NS-2 simulator, www.isi.edu/nanam/ns