论文标题
覆盖中的多径视频电话服务的基于在线学习的路径选择
An Online Learning Based Path Selection for Multipath Video Telephony Service in Overlay
论文作者
论文摘要
即使是实时视频电话服务也普遍应用，为用户提供令人满意的经验质量仍然是一项挑战任务，尤其是在无线网络中。多径传输是通过汇总带宽来提高视频质量的有前途的解决方案。在现有的多路径传输解决方案中，发件人同时将流量分配在默认路由路径上，并且没有灵活性选择路径。当默认路径陷入严重的拥塞并且可用的带宽下降时，发件人必须通过降低分辨率或编码比特率来降低视频质量。在当前基础架构中部署继电器服务器以形成覆盖网络提供路径多样性。采用基于多臂匪徒的在线学习方法用于选择路径以收获最大利润。此外，实施了由BBR适应的拥塞控制算法以探测带宽并避免连接拥塞。为了维持吞吐量稳定性和公平性，使用较小的探测器增益值，并且带宽探针阶段中的循环长度是随机的。为了减少延迟，将减少机上数据包，以与探针下阶段中估计的带宽延迟产品相匹配。进行实验以验证提出的解决方案的有效性，以改善视频通信服务的吞吐量和质量。
Even real time video telephony services have been pervasively applied, providing satisfactory quality of experience to users is still a challenge task especially in wireless networks. Multipath transmission is a promising solution to improve video quality by aggregating bandwidth. In existing multipath transmission solutions, sender concurrently splits traffic on default routing paths and has no flexibility to select paths. When default paths fall into severe congestion and the available bandwidth decreases, sender has to decrease video quality by reducing resolution or encoding bitrate. Deploying relay servers in current infrastructure to form overlay network provides path diversity. An online learning approach based on multi-armed bandits is applied for path selection to harvest maximum profit. Further, a congestion control algorithm adapted from BBR is implemented to probe bandwidth and to avoid link congestion. To maintain throughput stability and fairness, a smaller probe up gain value is used and the cycle length in bandwidth probe phase is randomized. To reduce delay, the inflight packets will be reduced to match with the estimated bandwidth delay product in the probe down phase. Experiments are conducted to verify the effectiveness the proposed solution to improve throughput and quality in video communication service.
