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Proceedings ArticleDOI

Confused, timid, and unstable: picking a video streaming rate is hard

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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.

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On delimiting video rebuffering for stream-switching adaptive applications

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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

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

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.
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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.