Mitigating Congestion with Decentralized Traffic Shaping for Adaptive Video Streaming over ICN
Tomoya Nakano, Rei Nakagawa, Nariyoshi Yamai · 2022
With a significant increase in video traffic on the Internet, Information Centric Networking (ICN), which improves the communication quality through decentralized content-based control, has been attracting attention. To improve the quality of experience (QoE) on video streaming, adaptive video streaming is applied to ICN. In adaptive streaming over ICN, the Adaptive Bitrate (ABR) algorithm, which adjusts a bitrate of the video segment according to a bandwidth estimation, is mainly responsible for a congestion control. However, since a bitrate is adjusted every time just before downloading a segment, even if congestion occurs in a network, it takes time for congestion avoidance until the current segment download finishes. To avoid congestion early, this paper presents decentralized congestion control in which a distributed server or router mitigates communication traffic immediately according to explicit congestion detection using transmission queue occupancy. Then, we propose the decentralized traffic shaping system in which the server or router increases a transmission interval between packets to be sent during congestion. Thus, the proposed method encourages the ABR algorithm to avoid congestion quickly by the reduced communication traffic according to explicit congestion detection. An experiment using the proposed method was implemented on ns-3 network simulator and results of experiments showed that play stall could be reduced without decreasing QoE.