Distributed rate allocation policies for multihomed video streaming over heterogeneous access networks

  • Authors:

  • Xiaoqing Zhu;Piyush Agrawal;Jatinder Pal Singh;Tansu Alpcan;Bernd Girod

  • Affiliations:

  • Department of Electrical Engineering, Stanford University, Stanford, CA;Department of Electrical Engineering, Stanford University, Stanford, CA;Deutsche Telekom Inc., R&D Lab, Los Altos, CA;Deutsche Telekom Laboratories, Berlin, Germany;Department of Electrical Engineering, Stanford University, Stanford, CA

  • Venue:
  • IEEE Transactions on Multimedia
  • Year:
  • 2009

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Abstract

We consider the problem of rate allocation among multiple simultaneous video streams sharing multiple heterogeneous access networks. We develop and evaluate an analytical framework for optimal rate allocation based on observed available bit rate (ABR) and round-trip time (RTT) over each access network and video distortion-rate (DR) characteristics. The rate allocation is formulated as a convex optimization problem that minimizes the total expected distortion of all video streams. We present a distributed approximation of its solution and compare its performance against H∞-optimal control and two heuristic schemes based on TCP-style additive-increase-multiplicative-decrease (AIMD) principles. The various rate allocation schemes are evaluated in simulations of multiple high-definition (HD) video streams sharing multiple access networks. Our results demonstrate that, in comparison with heuristic AIMD-based schemes, both media-aware allocation and and H∞ -optimal control benefit from proactive congestion avoidance and reduce the average packet loss rate from 45% to below 2%. Improvement in average received video quality ranges between 1.5 to 10.7 dB in PSNR for various background traffic loads and video playout deadlines. Media-aware allocation further exploits its knowledge of the video DR characteristics to achieve a more balanced video quality among all streams.