1 / 21 Network Characteristics of Video Streaming Traffic Ashwin Rao †, Yeon-sup Lim *, Chadi...
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Transcript of 1 / 21 Network Characteristics of Video Streaming Traffic Ashwin Rao †, Yeon-sup Lim *, Chadi...
1 / 21
Network Characteristics of Video Streaming Traffic
Ashwin Rao†, Yeon-sup Lim*, Chadi Barakat†, Arnaud Legout†, Don Towsley*, and Walid Dabbous†
†INRIA Sophia Antipolis France
*University of Massachusetts Amherst, USA
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Video Streaming Services
Containers
Desktop Browsers Native Mobile Applications
What are the Network Characteristics of Video Streaming Traffic?
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Objective
• What exactly happens during video streaming?– Arrival of data packets– Strategies to stream videos– Potential Impact
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• Introduction and Motivation• Datasets and Measurement Techniques• Streaming Strategies• Impact of Streaming Strategies
Outline
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Datasets
• YouTube videos– Flash, HTML5, and HD (Flash)– Mobile
• Netflix videos - Silverlight– Desktop – Mobile
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Measurement Locations
• France– Academic (Wired; Wi-fi for mobile)– Residential (Wi-fi)
• USA– Academic (Wired; Wi-fi for mobile)– Residential (Wired)
YouTube
YouTube and
Netflix
Similar Traffic Characteristics at Each Location
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Outline• Introduction and Motivation• Datasets and Measurement Techniques• Streaming Strategies• Impact of Streaming Strategies
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Generic Behavior of Video StreamingD
ownl
oad
Amou
nt
Time
Buf
ferin
gBlock Size
On
Off
Steady State
Average rate
∝
Video encoding rate
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We Identified Three Streaming Strategies
No On Off Cycles
Long On Off Cycles
OFF OFF
Short On Off Cycles
Streaming strategies vastly different
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Streaming Strategies UsedService YouTube Netflix
Container Flash HD (Flash) HTML5 Silverlight
IE 9 Short No Short Short
Firefox Short No No Short
Chrome Short No Long Short
iOS (native)
- - Based on encoding rate
Short
Android (native)
- - Long Long
Streaming strategy differs withapplication type and container
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Features Controlling Arrival of Data Packets
• Buffering Amount• Block Size• Accumulation Ratio
Average download rate in steady state phase
Video encoding rate=
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Arrival of Packets for Short ON OFF Strategy
64 kB
40 sec. of playback
Server side rate control with
absence of ACK clocks
1.25Buffering
independent ofencoding rate
Browser throttles rate
256 kB
Significant differences between implementations
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Outline• Introduction and Motivation• Datasets and Measurement Techniques• Streaming Strategies• Impact of Streaming Strategies
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Impact of Streaming StrategiesNo On Off Long On Off Short On Off
TCP Friendly Yes – TCP File Transfer
Yes – Periodic File Transfer
Unknown traffic not ack-clocked
Playout buffer occupancy
Large Moderate Small
Unused bytes on user interruptions
Large amount
Moderate amount
Small amount
StrategyMetric
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Model for Aggregate Rate of Streaming Traffic
• Objective– Capture statistical properties of aggregate
streaming trafficBarakat et al., A flow-based model for Internet backbone traffic, In IMW’02.
• Uses– Dimension the network– Quantify impact of user interruptions
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Aggregate Rate of Video Streaming Traffic
Aggregate Rate
Arrival Rate of streaming sessions
(Poisson)
Amount of datadownloaded
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Insights from Model
• No User Interruptions– Aggregate rate (mean, variance, etc.) independent
of streaming strategy– Dimensioning rules do not change– Strategy to optimize other goals (server load, etc.)
• Users Interruptions– Impact of buffering amount and accumulation
ratio on wasted bandwidth
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Summary
• Most popular clients and containers for video streaming
• Streaming strategy differs with client applications and container– HTML5 streaming vastly differs with client
applications• Model to study impact of streaming
strategies
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Open Questions for the CCN community
• Should CCN nodes be aware of the underlying streaming strategy?
• What is the optimal streaming strategy for CCN?
• Is there an optimal caching strategy for a given streaming strategy?
• What is the impact of user interruptions due to lack of interest on CCN caches?
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ACK Clocks
• Source sends packets on receiving ACK• ACKs as an indication of available
bandwidth46 packets sent in the first RTT after an OFF period of more than 500 ms
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Conclusion
• Most popular clients and containers for video streaming
• Streaming strategy differs with client applications and container– HTML5 streaming vastly differs with client
applications• Model to study impact of streaming
strategies
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User Interruptions
Video duration
Playback time downloaded in buffering phase
1 Accumulation ratio Fraction of video watched
- X>
Video download will be in progress when
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Netflix Streaming StrategiesContainer Silverlight Silverlight for Mobile Devices
Application Any Web Browser
iOS (native) Android (native)
Strategy Short Short Long
Buffering Amount
30 MB to 150 MB
10 to 20 MB 35 to 45 MB
Block Size 0.5 MB to 2 MB
0.5 to 2.5 MB 4.5 to 6 MB
B-30
YouTube Streaming StrategiesContainer Flash HTML5
Application Any Web Browser
IE 9 Firefox Google Chrome
iOS (native)
Android (native)
Strategy Short Short No Long Multiple Long
Buffering Amount
40 s Up to 15 MB
Video Size
Up to 15 MB
40 s of playback or up to 20 MB
Up to 10 MB
Block Size 64 kB 256 kB NA 5 MB to 8 MB
64 kB 2 MB to 8 MB
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Tradeoff
• Migration from one strategy to another can have a non-negligible impact
Raw File Transfer vs
Periodic Buffering vs
No ack-clock