A Method for Extremely Scalable and Low Demand Live P2P Streaming based on Variable Bitrate

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P2P Streaming: Models and Problems

M.Zhanikeev -- maratishe@gmail.com --

Extremely Scalable ... Live P2P Streaming based on Variable Bitrate -- http://tinyurl.com/marat131205 ---

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P2P Streaming Models
1.

◦ many software products
-- all based on default
BitTorrent

…
Share

BitTorrent model 11 ,
aka the pull paradigm

2.

Content
Provider
(origin)

P2P Network

substream model 10 ,
aka the push paradigm
◦ several existing services
07 08 09
◦ not limited to P2P
networks, also work in
clouds 03

03 myself+0 "Multi-Source Stream Aggregation in the Cloud" Wiley Book on Advanced Content Delivery ... Clouds (2013)
08 K.Park+4 "An Analysis of User Dynamics in P2P Live Streaming Services" ICC (2010)
09 C.Wu+2 "Diagnosing Network-wide P2P Live Streaming Inefficiencies" IEEE INFOCOM (2009)
10 Z.Li+4 "Towards Low-Redundancy Push-Pull P2P Live Streaming" QShine (2008)
11 C.Stais+1 "Realistic Media Streaming over BitTorrent" Future Network and Mobile Summit (2012)


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P2P Substream Method

….
P2P Connection

shake
hands than
use continuously

• basic idea:

….

….


….


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Problems and Solutions
•

quality management
1.
2.

•

overhead
1.
2.

•

BitTorrent: RTT per piece
substream: switching time at re-election

optimization
1.
2.

•

BitTorrent: nothing
substream: parent/child re-election

BitTorrent: nothing, but some selection algorithms
substream: multihop optimization is possible -- scheduling and flow problems

the biggest problem: data unit has constant size!



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P2P Streaming: Social Features



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P2P Streaming: Social Features
Scale

Traffic
flow

•

note: P2P delivery network is not really
a tree

• reality shows that your remote peers are

power-law distributed in throughput
◦ gets harder to find good peers with longer
lists

…
…
…
…



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Bitrate: CBR, VBR, SVC



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CBR, VBR, SVC
• VBR and SVC are both part of

ITU-T H264 12

VBR: really extreme variation in throughput
• SVC: smoother distribution 13 , with some control over smoothness 14
•

why: SVC is based on hierarchy of layers which can be moved around within GOP
Block

GOP

CBR
Time

Block

GOP
Frame size

Frame size

GOP

Frame size

◦

VBR
Time

Block

SVC
Time

12 "Advanced video coding for generic audiovisual services" ITU-T Recommendation H.264 (2012)
13 R.Kusching+2 "An Evaluation of TCP-based Rate-Control ... Streaming of H.264/SVC" ACM SIGMM MMsys) (2010)
14 M.Fidler+3 -M.Zhanikeev -- maratishe@gmail.com "Efficient Smoothing of Robust VBR ... LiveTraffic ... Slice-Based..." CCNC (2007)
Extremely Scalable Video P2P Streaming based on Variable Bitrate -- http://tinyurl.com/marat131205 ---

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Bitrate Models and Distributions

Frame size (kb)

•

real traces from 15
VBR versus single-layer SVC
SVC

12

12

Frame size (kb)

•

8
4
0
0

20
40
60
80
Time sequence

100

VBR

8
4
0
0

20
40
60
80 100
Distribution sequence

15 P.Seeling+2 "Network Performance Evaluation with Frame Size and Quality Traces ..." IEEE Comm. Surveys... (2004)


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The Proposal: VBR Subtreams



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Recap: The Objectives
.
The Main Objective is...
.
... to build a method which can
.

adapt to to any peer distribution in realtime

• VBR is fixed, no control parameter
• SVC can be controlled by switching between encoders

ultimately: raw manipulation by shifting SVC blocks around the GOP
• ideal success: distribution of throughput in peers = distribution of
•

framesize in GOP



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Proposal: Substream Design
•

simple:

pick a

frame position in GOP and assign it to one peer

◦ positions: 1st, 2nd, ....

•

expected outcome:

since 1st frame is normally the largest in GOP, that peer
should be able to support high throughput
◦ by extension, most other peers carry much lower load
◦ size of GOP = number of peers, by design

GOP

CBR
Time


Block

GOP
Frame size

Block
Frame size

Frame size

GOP

VBR
Time

Block

SVC
Time


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Proposal: Dynamics
Parent A

Client

Bigger frames
(GOP pos x)
Failed to
receive

Re -order
parents
Close
connection
Pick a
better
candidate

Parent B
Bigger frames
(GOP pos x)
Smaller frames
(GOP pos y)


traditional substream:

find a new peer for a substream
• proposed: swap frame
positions between two peers
Only for changed
frames/parents/GOP pos

Connection
close detected

•
Periodic
check/update

◦ peers are initially selected
close to the expected
distribution, so no new
peers are necessary


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Simulation



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Simulation: Models and Parameters
CBR
SVC
VBR

1

Value

0.8

1. pick VBR I-Frame size as
set it to 1

0.6

2. pick I-Frame size of SVC as a

0.4

3. pick frame size of SBR as a

fraction of 1
fraction of 1

0.2

4. use these fractions as

parameters

0
0

10


20
30
Distribution sequence

40

50


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Simulation: E2E Throughput Model
drops in throughput
longer paths experience more drops (not deeper!, more in number)
a parameter defines the range of drop probabilities for sampling one's peers

• throughput variation is modeled as
•
•

Throughput

Time slot

100%
Simulation
parameters
parameter


0%

Time


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Ratio of VBR/CBR and SVC/CBR (freeze time)

Results : Freeze Time
SVC to CBR
VBR to CBR

7
6

x=0.05

5

x=0.2

•

x=1

4
3

simple lesson:

framesize
distributions are good, as long
as they are not extreme

• CBR can outperform VBR/SVC

below frame size of
0.2 -- 1/5th of VBR I-Frame)
only

y=1

2
1
0
0

0.3


0.6
0.9
CBR level

1.2

1.5


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Throughput gain (higher / lower) (kbps)

Results : Gain (social)
1.9

•

1.7

SVC substream design?

Slow peers

1.5

viewpoint: how much can a
user benefit from a VBR/

• test various peer distributions

and find out

1.3

•

1.1

gain: best SVC/VBR
throughput divided by the
number of CBR

0.9
0.1

0.2

0.3
0.4
0.5
0.6
0.7
0.8
Normalized lower throughput


0.9

1


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Wrapup
•

VBR/SVC substream design create a socially
adequate method
◦ after all, is it your fault that your 3G shapes your throughput?

• VBR/SVC substream design has to be a

clean slate -- frame position

assignment is proposed
• results show that

is smoother

SVC is preferred because its framesize distribution

◦ even more becuase the distribution can, in theory, be controlled



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That’s all, thank you ...



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The PUSH vs PULL Argument
• mathematical argument in

[03]
Client

Server

Client

Server

Pull


overhead =
RTT for each piece

• overhead can be overcome

only by drastically
increasing the number of
remote peers --

Push
……

•

……

swarming


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Reference: Average Throughput
Ratio of average throughput (-log(1/y) for y < 1)

SVC/CBR

VBR/CBR

3

1

unit I-Frame size is
50kb
known fact: VBR/SVC can
support the same quality

0.5

at 1/2 of CBR's throughput 15

2.5

•

CBR < VBR

2

VBR < CBR

1.5

•

VBR < 0.5 * CBR

0

• 1/2 of CBR's throughput is at

about 20kb
framesize

-0.5
-1

of CBR

-1.5
0

10

20

30
40
50
CBR Frame Size (kb)

60

70

15 P.Seeling+2 "Network Performance Evaluation with Frame Size and Quality Traces ..." IEEE Comm. Surveys... (2004)


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Features: Taxonomy
• is your

data unit regular?
Content
BLOCK
GOP
FRAME

Fixed
Regular


adaptive in realtime?

GOP

BLOCK

FRE

and can it be

FIR

Fixed
Irregular

FRAME

Adaptive
Irregular
AIR

This
method


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SVC in P2P: Disclaimer
• SVC is considered for P2P in literature
1. BitTorrent with variable-size pieces 04
2. BitTorrent pieces as multiples of GOP 05
3. optimization for SVC layer repacking in small scale streaming tool called SPPM
(Stanford)
◦ assignment by frame size positions is still the unique contributions
◦ socially, the proposed method will scale while SPPM will not

04 N.Capovilla+4 "...Distributing Scalable Content over P2P Networks" MMEDIA (2010)
05 P.Baccichet+3 "Low-delay Peer-to-Peer Streaming using Scalable Video Coding" Packet Video (2007)


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[01] R.Buyya+3 (2008)
Content Delivery Networks
Springer LNEE, vol.9
[03] myself+0 (2013)
Multi-Source Stream Aggregation in the Cloud
Wiley Book on Advanced Content Delivery ... Clouds
[04] N.Capovilla+4 (2010)
...Distributing Scalable Content over P2P Networks
MMEDIA
[05] P.Baccichet+3 (2007)
Low-delay Peer-to-Peer Streaming using Scalable Video Coding
Packet Video
[06] C.Gurler+2 (2012)
Variable chunk size ... and ... window for P2P streaming of scalable video
ICIP


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[07] B.Li+5 (2008)
Inside the New Coolstreaming: Principles, Measurements and Performance
Implications
IEEE INFOCOM
[08] K.Park+4 (2010)
An Analysis of User Dynamics in P2P Live Streaming Services
ICC
[09] C.Wu+2 (2009)
Diagnosing Network-wide P2P Live Streaming Inefficiencies
IEEE INFOCOM
[10] Z.Li+4 (2008)
Towards Low-Redundancy Push-Pull P2P Live Streaming
QShine
[11] C.Stais+1 (2012)
Realistic Media Streaming over BitTorrent
Future Network and Mobile Summit


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[12]

(2012)
Advanced video coding for generic audiovisual services
ITU-T Recommendation H.264

[13] R.Kusching+2 (2010)
An Evaluation of TCP-based Rate-Control ... Streaming of H.264/SVC
ACM SIGMM MMsys)
[14] M.Fidler+3 (2007)
Efficient Smoothing of Robust VBR Video Traffic ... Slice-Based...
CCNC
[15] P.Seeling+2 (2004)
Network Performance Evaluation with Frame Size and Quality Traces ...
IEEE Comm. Surveys...
[16] J.Surowiecki (2004)
The Wisdom of Crowds
Doubleday


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A Method for Extremely Scalable and Low Demand Live P2P Streaming based on Variable Bitrate

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