Exstream: A Delay-minimized Streaming System with Explicit Frame Queueing Delay Measurement
Shinik Park, Sanghyun Han, Junseon Kim, Jongyun Lee, Sangtae Ha, Kyunghan Lee
摘要
Network fluctuations can cause unpredictable degradation of the user’s quality of experience (QoE) on real-time video streaming. The intrinsic property of real-time video streaming, which generates delay-sensitive and chunk-based video frames, makes the situation even more complicated. Although previous approaches have tried to alleviate this problem by controlling the video bitrate based on the current network capacity estimate, they do not take into account the explicit queueing delay experienced by the video frame in determining the bitrate of upcoming video frames. To tackle this problem, we propose a new real-time video streaming system, Exstream, that can adapt to dynamic network conditions with the help of video bitrate control method and bandwidth estimation method designed to support real-time video streaming environments. Exstream explicitly estimates the queueing delay experienced by the video frame based on the transmission time budget that each frame can maximally utilize, which depends on the frame generation interval, and adjusts the bitrate of newly generated video frames to suppress the queueing delay level close to zero. Our comprehensive experiments demonstrate that Exstream achieves lower frame delay than four existing systems, Salsify, WebRTC, Skype, and Hangouts without frequent video frame skip.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- PDStream: Slashing Long- Tail Delay in Interactive Video Streaming via Pseudo-Dual StreamingXuedou Xiao, Yingying Zuo, Mingxuan Yan, Kezhong Liu 等INFOCOM 2025 · 被引用 1 次
- SJA: Server-driven Joint Adaptation of Loss and Bitrate for Multi-Party Realtime Video StreamingKai Shen, Dayou Zhang, Zi Zhu, Lei Zhang 等INFOCOM 2023 · 被引用 7 次
- Reparo: QoE-Aware Live Video Streaming in Low-Rate Networks by Intelligent Frame RecoveryFulin Wang, Qing Li, Wanxin Shi, Gareth Tyson 等ACM MM 2023 · 被引用 10 次
- An Intelligent Learning Approach to Achieve Near-Second Low-Latency Live Video Streaming under Highly Fluctuating NetworksGuanghui Zhang, Ke Liu, Mengbai Xiao, Bingshu Wang 等ACM MM 2023 · 被引用 5 次
- Camel: Frame-Level Bandwidth Estimation for Low-Latency Live Streaming under Video Bitrate UndershootingLiming Liu, Zhidong Jia, Li Jiang, Wei Zhang 等WWW 2026
