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
1 / 21
Video Streaming Services
Containers
What are the Network Characteristics
Desktop Browsers
Native Mobile
of Video Streaming Traffic?
Applications
2 / 21
Objective
• What exactly happens during video
streaming?
– Arrival of data packets
– Strategies to stream videos
– Potential Impact
3 / 21
Outline
• Introduction and Motivation
• Datasets and Measurement Techniques
• Streaming Strategies
• Impact of Streaming Strategies
4 / 21
Datasets
• YouTube videos
– Flash, HTML5, and HD (Flash)
– Mobile
• Netflix videos - Silverlight
– Desktop
– Mobile
5 / 21
Measurement Technique
Packet Capture
802.11
6 / 21
Measurement Locations
• France
– Academic (Wired; Wi-fi for mobile)
– Residential (Wi-fi)
YouTube
– Academic (Wired; Wi-fi for mobile)
– Residential (Wired)
and
Netflix
Similar Traffic Characteristics at
• USA
Each Location
YouTube
7 / 21
Outline
• Introduction and Motivation
• Datasets and Measurement Techniques
• Streaming Strategies
• Impact of Streaming Strategies
8 / 21
Download Amount
Generic Behavior of Video Streaming
Off
Block Size
Time
9 / 21
We Identified Three Streaming
Strategies
No On Off
Cycles
On Off
Streaming strategiesShort
vastly
Cycles
different
Long On Off
Cycles
OFF
OFF
10 / 21
Streaming Strategies Used
Service
YouTube
Netflix
Container
Flash
HD (Flash)
HTML5
Silverlight
IE 9
Short
No
Short
Short
Firefox
Short
No
No
Short
Streaming
strategy
differs with
Short
No
Long
Short
iOS
Based container
on
Short
application
type
and
(native)
Chrome
encoding rate
Android
-
-
Long
Long
(native)
11 / 21
Features Controlling Arrival of Data
Packets
• Buffering Amount
• Block Size
• Accumulation Ratio
=
Average download rate in steady state phase
Video encoding rate
12 / 21
Arrival of Packets for Short ON OFF
Strategy
64 kB
40 sec. of playback
Buffering
independent of
encoding rate
Significant differencesBrowser
between
throttles rate
Server side
rate
implementations
control with
absence of ACK
clocks
256
kB
13 / 21
Outline
• Introduction and Motivation
• Datasets and Measurement Techniques
• Streaming Strategies
• Impact of Streaming Strategies
14 / 21
Impact of Streaming Strategies
Strategy
Metric
TCP Friendly
Playout buffer
occupancy
Unused bytes on
user interruptions
No On Off
Long On Off
Short On Off
Yes – TCP File
Yes – Periodic
Unknown traffic
Transfer
File Transfer
not ack-clocked
Large
Moderate
Small
Large
amount
Moderate
amount
Small amount
15 / 21
Model for Aggregate Rate of Streaming
Traffic
• Objective
– Capture statistical properties of aggregate
streaming traffic
Barakat et al., A flow-based model for Internet
backbone traffic, In IMW’02.
• Uses
– Dimension the network
– Quantify impact of user interruptions
16 / 21
Aggregate Rate of Video Streaming
Traffic
Aggregate Rate
Arrival Rate of
streaming sessions
(Poisson)
Amount of data
downloaded
17 / 21
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
18 / 21
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
19 / 21
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?
20 / 21
Network Characteristics
of Video Streaming Traffic
THANK YOU
ashwin.rao@inria.fr
21 / 21
BACKUPS
B-22
Short or Long
• Block Size – Threshold 2.5 MB
Long Long
Short
OFF
B-23
ACK Clocks
• Source sends packets on receiving ACK
• ACKs as an indication of available
bandwidth
46 packets sent in
the first RTT after
an OFF period of
more than 500 ms
B-24
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
25 / 21
User Interruptions
Video download will be in progress when
Video
duration
Playback time downloaded in buffering phase
>
1 - Accumulation ratio X Fraction of video
watched
B-26
Impact of Losses
• Merging of cycles
• Playback can freeze
• Longer buffering phase
B-27
HTML5
• Primary - webM
• Very few - h.264
B-28
Netflix Streaming Strategies
Container
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-29
YouTube Streaming Strategies
Container
Flash
Application Any Web
Browser
HTML5
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
B-30
Tradeoff
• Migration from one strategy to another
can have a non-negligible impact
Raw File Transfer
vs
Periodic Buffering
vs
No ack-clock
B-31
Video Streaming in the Internet
• 20 % to 40 % of all Internet traffic
– Traffic share steadily increasing in recent
years
• Streaming over HTTP – using TCP
– Firewall configurations
– TCP flows assumed to be fair
B-32