加速反馈控制,实现 ICN 上自适应视频流的 QoE 公平性

Rei Nakagawa, S. Ohzahata, Ryo Yamamoto
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引用次数: 0

摘要

如今,以信息为中心的网络使自适应视频流客户端能够通过应用灵活的基于内容的控制来进一步改善 QoE。然而,自适应比特率算法会使客户端以过高的比特率占用瓶颈链路,从而降低共享瓶颈链路的其他客户端的 QoE 公平性。因此,我们提出了一种基于比特率的加速反馈控制方法--公平比特率(fairAccel),以实现 QoE 公平性。公平比特率会为选择较低比特率的客户端分配更多带宽,同时抑制在瓶颈链路上选择最高比特率的客户端的内容请求。此外,为了进一步提高 QoE 公平性,fairAccel 还利用了 ICN 内容请求/响应的对称路由,并对内容请求/响应路径进行双向反馈控制。这样,fairAccel 就能在过多流量被传送到响应路径之前,通过抑制内容请求来控制路由器队列,从而加速反馈控制。通过模拟实验,fairAccel 提高了平均比特率,并进一步改善了代表性 ABR 算法的 QoE 公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accelerating Feedback Control for QoE Fairness in Adaptive Video Streaming Over ICN
Today, information centric networking enables adaptive video streaming clients to further improve QoE by applying flexible content-based control. However, an adaptive bitrate algorithm makes a client occupy the bottleneck link at excessively high bitrate, reducing the QoE fairness to other clients sharing the bottleneck link. Then, we propose fairAccel, a method of accelerating bitrate-based feedback control for achieving QoE fairness. fairAccel assigns more bandwidth to clients selecting the lower bitrate while suppressing content requests from clients selecting the highest bitrate on the bottleneck link. In addition, to further improve QoE fairness, fairAccel exploits the symmetric routing of ICN content request / response and applies bidirectional feedback control to the content request / response path. Thus, fairAccel accelerates feedback control by mitigating router queues under control of suppressing content requests before excessive traffic is delivered to the response path. Through simulation experiments, fairAccel improves the average bitrate and further improves QoE fairness for representative ABR algorithms.
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