Xiaoqing Zhu
ABSTRACT
Contemporary wireless devices integrate multiple networking technologies, such as cellular, WiMax and IEEE 802.11a/b/g, as alternative means of accessing the Internet. Efficient utilization of available bandwidth over heterogeneous access networks is important, especially for media streaming applications with high data rates and stringent delay requirements. In this work we consider the problem of rate allocation among multiple video streaming sessions sharing multiple access networks. We develop and evaluate an analytical framework for optimal video rate allocation, based on observed available bit rate (ABR) and round trip time (RTT) over each access network, as well as the video distortion-rate (DR) characteristics. The rate allocation is formulated as a convex optimization problem that minimizes the sum of expected distortion of all video streams. We then present a distributed approximation of the optimization, which enables autonomous rate allocation at each device in a media- and network-aware fashion. Performance of the proposed allocation scheme is compared against robust rate control based on H∞ optimal control and two heuristic schemes employing TCP style additive-increase-multiplicative-decrease (AIMD) principles. Wesimulate in NS-2 [1] simultaneous streaming of multiple high-definition(HD) video streams over multiple access networks, using ABR and RTT traces collected on Ethernet, IEEE 802.11g, and IEEE 802.11b networks deployed in a corporate environment. In comparison with heuristic AIMD-based schemes, rate allocation from both the media-aware convex optimization scheme and H∞ optimal control benefit from proactive avoidance of network congestion, and can reduce the average packet loss ratio from 27% to below 2%, while improving the average received video quality by 3.3 - 4.5 dB in PSNR.
Supplemental Material
- "NS--2," http://www.isi.edu/nsnam/ns/.Google Scholar
- P. Vidales, J. Baliosion, J. Serrat, G. Mapp, F. Stejano, and A. Hopper, "Autonomic sytem for mobility support in 4G networks," in IEEE Journal on Selcted Areas in Communications, Dec. 2005, vol. 23, pp. 2288--2304. Google ScholarDigital Library
- "IEEE 802.21," http://www.ieee802.org/21/.Google Scholar
- A. Cuevas, J. I. Moreno, P. Vidales, and H. Einsiedler, "The IMS platform: A solution for next generation network operators to be more than bit pipes," in IEEE Communications Magazine, Issue on Advances of Service Platform Technologies, Aug. 2006, vol. 44, pp. 75--81. Google ScholarDigital Library
- V. Jacobson, "Congestion avoidence and control," in Proc. SIGCOMM'88, Aug. 1988, vol. 18, pp. 314--329. Google ScholarDigital Library
- M. Allman, V. Paxson, and W. R. Stevens, TCP Congestion Control, RFC 2581, Apr. 1999. Google ScholarDigital Library
- S. Floyd and K. Fall, "Promoting the use of end-to-end congestion control in the Internet," IEEE/ACM Trans. on Networking, vol. 7, no. 4, pp. 458--472, Aug. 1999. Google ScholarDigital Library
- M. Handley, S. Floyd, J. Pahdye, and J. Widmer, TCP Friendly Rate Control (TFRC): Protocol Specification, RFC 3448, Jan. 2003. Google ScholarDigital Library
- Z. Wang, S. Banerjee, and S. Jamin, "Media-friendliness of a slowly-responsive congestion control protocol," in Proc. 14th International Workshop on Network and Operating Systems Support for Digital Audio and Video, Cork, Ireland, 2004, pp. 82--87. Google ScholarDigital Library
- F. Kelly, A. Maulloo, and D. Tan, "Rate control for communication networks: Shadow prices, proportional fairness and stability," Journal of Operations Research Society, vol. 49, no. 3, pp. 237--252, 1998.Google ScholarCross Ref
- H. Yaiche, R. Mazumdar, and C. Rosenburg, "A game theoretic framework for bandwidth allocation and pricing in broadband networks," IEEE/ACM Trans. on Networking, vol. 8, no. 5, pp. 667--678, Oct. 2000. Google ScholarDigital Library
- T. Alpcan and T. Başar, "A utility-based congestion control scheme for Internet-style networks with delay," IEEE Trans. on Networking, vol. 13, no. 6, pp. 1261--1274, December 2005. Google ScholarDigital Library
- T. Alpcan and T. Basar, "Global stability analysis of an end-to-end congestion control scheme for general topology networks with delay," in Proc. 42nd IEEE Conference on Decision and Control (CDC'03), Maui, HI, U.S.A., Dec. 2003, pp. 1092--1097.Google Scholar
- S. Shakkottai, E. Altman, and A. Kumar, "The case for non-cooperative multihoming of users to access points in IEEE 802.11 WLANs," in Proc. IEEE INFOCOM'06, Barcelona, Spain, Apr. 2006, pp. 1--12.Google Scholar
- A. Szwabe, A. Schorr, F. J. Hauck, and A. J. Kassler, "Dynamic multimedia stream adaptation and rate control for heterogeneous networks," in Proc. 15th International Packet Video Workshop, (PV'06), Hangzhou, China, May 2006, vol. 7, pp. 63--69.Google Scholar
- D. Jurca and P. Frossard, "Media-specific rate allocation in heterogeneous wireless networks," in Proc. 15th International Packet Video Workshop, (PV'06), Hangzhou, China, May 2006, vol. 7, pp.713--726.Google Scholar
- X. Zhu, J. P. Singh, and B. Girod, "Joint routing and rate allocation for multiple video streams in ad hoc wireless networks," in Proc. 15th International Packet Video Workshop, (PV'06), Hangzhou, China, May 2006, vol. 7, pp. 727--736.Google Scholar
- J. P. Singh, T. Alpcan, P. Agrawal, and V. Sharma, "An optimal flow assignment framework for heterogeneous network access," in Proc. IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, Helsinki, Finland, Apr. 2007.Google ScholarCross Ref
- T. Alpcan, J. P. Singh, and T. Basar, "A robust flow control framework for heterogenous network access," in Proc. 5th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Limassol, Cyprus, June 2007.Google ScholarCross Ref
- L. Kleinrock, Queuing Systems, Volume II: Computer Applications, Wiley Interscience, New York, USA, 1976.Google Scholar
- K. Stuhlmüller, N. Färber, M. Link, and B. Girod, "Analysis of video transmission over lossy channels," IEEE Journal on Selected Areas in Communications, vol. 18, no. 6, pp. 1012--1032, June 2000. Google ScholarDigital Library
- X. Zhu, E. Setton, and B. Girod, "Congestion-distortion optimized video transmission over ad hoc networks," EURASIP Journal of Signal Processing: Image Communications, vol. 20, no. 8, pp. 773--783, Sept. 2005.Google ScholarCross Ref
- S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, United Kindom, 2004. Google ScholarDigital Library
- T. Basar and P. Bernhard, H∞-Optimal Control and Related Minimax Design Problmes: A Dynamic Game Approach, Birkhaüser, Boston, MA, 1995.Google Scholar
- Jiri Navratil and R. Les. Cottrell, "Abing," http://www-iepm.slac.stanford.edu/tools/abing/.Google Scholar
- ITU-T and ISO/IEC JTC 1, Advanced Video Coding for Generic Audiovisual services, ITU-T Recommendation H.264 - ISO/IEC 14496-10(AVC), 2003.Google Scholar
- "x.264," http://developers.videolan.org/x264.html.Google Scholar
Index Terms
- Rate allocation for multi-user video streaming over heterogenous access networks
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