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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Proceedings ArticleDOI
Understanding the intermittent traffic pattern of HTTP video streaming over wireless networks
TL;DR: It is argued that through a deep understanding and careful analysis of the HTTPs video traffic, valuable information about the competing streams can be obtained and could be utilized in developing a network based solution that can significantly improve the video QoE and assist the video players to perform much better.
Proceedings ArticleDOI
MASH: A rate adaptation algorithm for multiview video streaming over HTTP
Khaled Diab,Mohamed Hefeeda +1 more
TL;DR: MASH can produce much higher and smoother quality than the algorithm used by YouTube, while it is more efficient in using the network bandwidth, and large-scale experiments show that MASH maintains fairness across competing sessions, and it does not overload the streaming server.
Journal ArticleDOI
Server side, play buffer based quality control for adaptive media streaming
TL;DR: This paper demonstrates that the drawbacks of existing protocols can be overcome with a server side, buffer based quality control scheme and achieves this without client assistance by designing a play buffer estimation algorithm.
Journal ArticleDOI
SABA: segment and buffer aware rate adaptation algorithm for streaming over HTTP
Waqas ur Rahman,Kwangsue Chung +1 more
TL;DR: This paper proposes a throughput estimation method that accurately estimates the throughput based on previous throughput samples, and is robust to short term and small fluctuations, and sensitive to large fluctuations in throughput.
References
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Proceedings ArticleDOI
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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.