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Rate control and stream adaptation for scalable video streaming over multiple access networks

机译:速率控制和流自适应,用于通过多路访问网络进行可伸缩视频流

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In a multihomed video streaming system, a video sequence is simultaneously transmitted over multiple access networks to a client. In this paper, we formulate the rate control and stream adaptation problems into a unified optimization problem, which determines the sending rates of individual networks, selects which video packets to transmit, and assigns each packet to an access network. We propose two heuristic algorithms with a trade-off between optimality and computational complexity. One of the proposed algorithms runs faster, while the other one results in better video quality. We propose a hybrid algorithm that demonstrates a good balance between optimality and computational complexity. We conduct extensive packet-level simulations to evaluate our algorithms using real network conditions and actual scalable video streams. We compare our algorithms against the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) standard. The simulation results show that our algorithms significantly outperform current systems while being TCP-friendly. Our algorithms achieve at least 10 dB quality improvement over DCCP and result in up to 83% packet delivery delay reduction.
机译:在多宿主视频流系统中,视频序列同时通过多个访问网络传输到客户端。在本文中,我们将速率控制和流自适应问题公式化为一个统一的优化问题,该问题确定各个网络的发送速率,选择要传输的视频数据包,并将每个数据包分配给接入网络。我们提出了两种启发式算法,需要在最优性和计算复杂性之间进行权衡。提出的一种算法运行速度更快,而另一种算法则可以提供更好的视频质量。我们提出了一种混合算法,该算法演示了最佳性和计算复杂性之间的良好平衡。我们进行了广泛的数据包级仿真,以使用真实的网络条件和实际的可伸缩视频流来评估我们的算法。我们将我们的算法与数据报拥塞控制协议(DCCP)标准中定义的速率控制算法进行了比较。仿真结果表明,我们的算法在对TCP友好的同时,性能明显优于当前系统。我们的算法比DCCP至少提高了10 dB的质量,并减少了83%的数据包传递延迟。

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