Virtualized End-to-End Management Functions for Aggregated Control of Video Traffic Flows

被引:0
|
作者
Ravindran, Kaliappa [1 ]
Cherian, Ancy [1 ]
Adiththan, Arun [1 ]
机构
[1] CUNY City Coll, New York, NY 10031 USA
来源
Q2SWINET'18: PROCEEDINGS OF THE 14TH ACM INTERNATIONAL SYMPOSIUM ON QOS AND SECURITY FOR WIRELESS AND MOBILE NETWORKS | 2018年
关键词
AIMD-based Rate Control; Quality of Adaptation; Scalable Video Encoding; Multi-step Congestion Recovery;
D O I
10.1145/3267129.3267142
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The paper describes the management and control (M&C) functions of various network nodes in an end-to-end rate-adaptive video transport system. Mobile user devices download video clips by sharing the underlying network path from an ingress node. At the core software level, M&C functions realize the well-known AIMD (additive increase multiplicative decrease) based video rate control algorithm to handle congestion along the path. AIMD is exercised on the aggregated data flows at a source ingress node based on the 'loss reports' signaled from the receiver egress node. Our aggregated AIMD-based control reduces the signaling overhead, relative to the existing approaches that anchor an AIMD instance on each user device itself. This offers scalability, while improving the user-experienced QoS: namely, low jitter in transfer rate, fast convergence to a final rate, and fair sharing of bandwidth. The offloading of aggregated AIMD-based control to the in-network overlay nodes also allows a reduction in the overall bandwidth usage. The software handling of 'last-mile' issues in the path between user devices and egress nodes (such as greedy users and access network channel sharing) are discussed, in a context of fine-granular video encoders in the devices. The paper also shows a virtualization of our M&C functions (as VNF modules) for deployment in large-scale video distribution networks: such as YouTube.
引用
收藏
页码:130 / 139
页数:10
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