论文标题
通过网络计算改善拥挤网络中的内容感知视频流
Improving Content-Aware Video Streaming in Congested Networks with In-Network Computing
论文作者
论文摘要
网络拥堵和数据包损失对视频流构成了不断增加的挑战。尽管为使视频编码方案的研究做出了研究，但转发设备尚未考虑监视数据包内容以确定数据包的优先级，并最大程度地减少了数据包丢失对视频传输的影响。在这项工作中，我们提倡使用数据包滴算法和网络内硬件模块来设计用于改善拥挤网络中内容感知视频流的解决方案的网络计算。结果表明，我们的方法可以将预测的数据包损失减少80％以上，而资源使用率和性能成本微不足道。
Network congestion and packet loss pose an ever-increasing challenge to video streaming. Despite the research efforts toward making video encoding schemes resilient to lossy network conditions, forwarding devices have not considered monitoring packet content to prioritize packets and minimize the impact of packet loss on video transmission. In this work, we advocate in favor of in-network computing employing a packet drop algorithm and an in-network hardware module to devise a solution for improving content-aware video streaming in congested network. Results show that our approach can reduce intra-predicted packet loss by over 80% at negligible resource usage and performance costs.
