Proceedings ArticleDOI
Confused, timid, and unstable: picking a video streaming rate is hard
Te-Yuan Huang,Nikhil Handigol,Brandon Heller,Nick McKeown,Ramesh Johari +4 more
- pp 225-238
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TLDR
This work measures three popular video streaming services -- Hulu, Netflix, and Vudu -- and finds that accurate client-side bandwidth estimation above the HTTP layer is hard, and rate selection based on inaccurate estimates can trigger a feedback loop, leading to undesirably variable and low-quality video.Abstract:
Today's commercial video streaming services use dynamic rate selection to provide a high-quality user experience. Most services host content on standard HTTP servers in CDNs, so rate selection must occur at the client. We measure three popular video streaming services -- Hulu, Netflix, and Vudu -- and find that accurate client-side bandwidth estimation above the HTTP layer is hard. As a result, rate selection based on inaccurate estimates can trigger a feedback loop, leading to undesirably variable and low-quality video. We call this phenomenon the "downward spiral effect", and we measure it on all three services, present insights into its root causes, and validate initial solutions to prevent it.read more
Citations
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Journal ArticleDOI
XMAS: An Efficient Mobile Adaptive Streaming Scheme Based on Traffic Shaping
Seohyang Kim,Chong-kwon Kim +1 more
TL;DR: A novel client-based traffic shaping scheme that effectively throttles server's packet transmission called XMAS is proposed for efficient video streaming in wireless networks and achieves up to 20% increase in average video rates while reducing rebuffer rates significantly.
Posted Content
Using the Buffer to Avoid Rebuffers: Evidence from a Large Video Streaming Service
TL;DR: This paper presents a class of "buffer-based" rate selection algorithms that reduce the rebuffering rate while allowing us to control the delivered video quality and shows that by doing away with estimating network capacity and instead focusing on buffer occupancy, this paper can reduce rebuffer rates by 20% while holding video rate constant.
Proceedings ArticleDOI
CSI: inferring mobile ABR video adaptation behavior under HTTPS and QUIC
TL;DR: This work develops CSI (Chunk Sequence Inferencer), a general system that enables third-parties to conduct active measurements and infer mobile ABR video adaptation behavior based on packet size and timing information still available in the encrypted traffic.
Journal ArticleDOI
TCLiVi: Transmission Control in Live Video Streaming Based on Deep Reinforcement Learning
TL;DR: TCLiVi significantly improves the video quality and decreases the rebuffering time, consequently increasing the QoE score by 40.84% in average, and is self-adaptive in different scenarios.
Proceedings ArticleDOI
Hindsight: evaluate video bitrate adaptation at scale
TL;DR: Hindsight is proposed, a linear-time and linear-space greedy algorithm that approximates the optimal ABR solution within a reasonable error bound that allows Hindsight to be computed and deployed at Netflix, providing a tool to identify sessions with suboptimal ABR performance.
References
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TCP Congestion Control
TL;DR: This document defines TCP's four intertwined congestion control algorithms: slow start, congestion avoidance, fast retransmit, and fast recovery, as well as discussing various acknowledgment generation methods.
Proceedings ArticleDOI
Youtube traffic characterization: a view from the edge
TL;DR: This paper presents a traffic characterization study of the popular video sharing service, YouTube, and finds that as with the traditional Web, caching could improve the end user experience, reduce network bandwidth consumption, and reduce the load on YouTube's core server infrastructure.
Proceedings ArticleDOI
An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP
TL;DR: This paper focuses on the rate-adaptation mechanisms of adaptive streaming and experimentally evaluates two major commercial players (Smooth Streaming, Netflix) and one open source player (OSMF).
Proceedings ArticleDOI
Understanding the impact of video quality on user engagement
Florin Dobrian,Vyas Sekar,Asad Awan,Ion Stoica,Dilip Antony Joseph,Aditya Ravikumar Ganjam,Jibin Zhan,Hui Zhang +7 more
TL;DR: This paper uses a unique dataset that spans different content types, including short video on demand, long VoD, and live content from popular video con- tent providers, to measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events.
Proceedings ArticleDOI
Unreeling netflix: Understanding and improving multi-CDN movie delivery
Vijay Kumar Adhikari,Yang Guo,Fang Hao,Matteo Varvello,Volker Hilt,Moritz Steiner,Zhi-Li Zhang +6 more
TL;DR: A measurement study of Netflix is performed to uncover its architecture and service strategy, and finds that Netflix employs a blend of data centers and Content Delivery Networks (CDNs) for content distribution.