network_coding_media
TRANSCRIPT
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On Network Coding Based Multirate Video Streaming in Dire
cted Networks
Chenguang Xu and Yinlong XuUniversity of Science and Technology of China
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Outline
• Multirate Video streaming• About Network coding• Related works
– Without network coding– With network coding
• My work• Future work
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Multirate Video Streaming • Property of Internet
– Heterogeneity of Receivers• Approaches:
– The replicated stream approach– Cumulative Layer approach, Such as MPEG
x (Layered Coding)– Non-cumulative Layer approach, Such as
MDC
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An example of Layer Coding
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What is Network Coding?
Transmission with network codingPacket level encoding at intermediate
nodesDecoding at receivers
The common method of network coding Linear Coding
E.g. 2a+3b
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An example -Network Coding
T1 F1
T3
F3
F2
T2
S?
a
aa
b b
b
a+b
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The advantages of Network Coding in Multicasting cont
Advantages: Throughput, Delay, Disadvantages: Packets Overhead(3%) Encoding/Decoding Time It
depends…
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Related works-Streaming Without Network Coding
Layered multicast streaming without network coding Rate allocation for each layer
Fairness Issues Adaptive layer receiving
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Related works-Streaming With Network Coding
Layered streaming with network coding “On multirate multicast streaming using network coding” A
llerton05 Encode the packets of different layers Objective: Maximize the total rates of receivers
Weakness: May cause ineffective transmission. Receiving higher layers while missing some lower layers .
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My work-The Unachievabilityof Network Coding for Streaming
layer1
layer1
?k1*a+k2*b+k3*c+k4*d
{a, b, c, d}
m1*a+m2*b+m3*c+m4*d
Layer1 {a, c}Layer2 {b, d}2 time units as a generation
Conventional Content Distribution Streaming
k1*a+k2*b+k3*c+k4*d
m1*a+m2*b+m3*c+m4*d
1 2 3 4
1 2 3 4
* * * *
* * * *
k a k b k c k d
m a m b m c m d
For T1 and T2
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Problem Descriptions
The Model1) Directed Networks G(V,E,c)2) a set of layers {Layer 1, Layer 2,…Layer k} ,
with a fixed rate rm for layer m3) R is the receivers’ set
Objective : Maximizing the total layers received
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Basic Assumptions
• Each encoding generation occupying Δ consecutive time units.
• The buffer is large enough and the link state is stable.
• Acyclic network• Fixed rate for each layer
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The Coding Scheme- LSNC
• Layered Separated Network Coding
• The Advantages of LSNC The advantage of network coding
Layer Separated for different priorities of layers Needn’t to pad the shorter packets with 0s
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The Coding Scheme- LSNC cont
The remaining problems:1. How to determine the layer for each
receiver?2. How to allocate bandwidth for each layer?3. How to achieve the rate of each layer?
By existed network coding algorithm
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Optimal Layer Separated Network Coding
OLSNC: Jointly Solve 1 and 2.( )
1 1
1 2 2 3, ( ) 1 ( )
( , ) ( , )
{ |( , )
, , (1)
0 1 ,1 ( ) (2)
0
i
i i
j i
OL vm
iji j
i i i i iOL v iOL v i
ij i i
l t l tij ji
j v v
Maximize
Subject to
for v R
or for v R j OL v
x x
0
{ |( , ) } }
( , )
{ |( , ) }
( , )0
{ |( , ) }
, 0, , 1 ( ) (3)
* , 1 ( ) (4)
,
i j
j i
j
j v v E E
t t
l iji il l i i
j v v E
l tj tl l t
j v v E
for i t i v R l OL v
x r for v R l OL v
x r for v R
( , )
1 ( ) (5)
( , ) , ,1 ( )
( , ) (6)
ij
t
l l tij i j t t
lij i j
l
l OL v
Y x for v v E v R l OL v
Y C v v
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OLSNC-An exampleS is the source. T1 and T2 are receivers.The stream is consisted of 3 layers-L1, L2, L3, with rate of 1, 1, 1 respectively.
By OLSNC, T1 can get 2 layers, and T2 can get 3 layers.
{L1} {L1} {L2} {L2}
{L3}
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OLSNC-An exampleWithout Network Coding:
Optimal Multicast Tree: T1 : 1 layerT2 : 2 layers
Optimal Multicast Sub-graph: T1 : 2 layersT2 : 2 layers
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Discussion on OLSNC
• Optimal result for LSNC • High Computing Complexity E.g. 15 receivers, 5 layers, worst
cast execution time is over 1 hour
• A time efficient algorithm is needed
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Sub-optimal Layer Separated Network Coding
Main Idea: 1) Allocate the bandwidth for each layer from low to high, with the objective of maximizing the aggregated maxflows
of receivers for rest higher layers. 2) Achieve the multicast rate for each layer with the bandwi
dth allocated by existed network coding algorithm.
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*
1
( , ) ( , )
{ |( , ) } { |( , ) }
0
, , , 0 (1)
t
i j j i
lt
v T
l t l tij ji
j v v E j v v E
i t
j
Max f
Subject to
x x
for v T v T t i i
x
0
( , )
{ |( , ) }
( , )0
{ |( , ) }
( , )
( 1, ) ( 1, )
{ |( { |( , ) }
(2)
(3)
, ( , )
0
j t
j
ij
i j i
l tt l t
j v v E
l tj l t
j v v E
l l tij t i j
l t l tij ji
j v j v v E
r for v T
x r for v T
Y x for v T v v E
x x
0
, ) }
* *
( 1, ) 1 *
{ |( , ) }
( 1, ) 1 *0
{ |( , ) }
1 ( 1, ) *
, , , 0 (4)
(5)
(6)
, ( ,
j
j t
j
ij
v E
i t
l t ljt t t
j v v E
l t lj t t
j v v E
l l tij t i
for v T v T t i i
x f for v T
x f for v T
Z x for v T v v
1
)
( , ) ( , ) (7)ij ij
j
l li j i j
E
Y Z C v v for v v E
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Performance Evaluation
Simulation Environments V= {v0, v1,…v10}, R={v1, v2,…v10} Two topologies: E1={(vi,vj)| i < j }, E2=((vi,vj)| 0 < j−i ≤ 2 } Two layer rate allocation schemes: Flat and Exponential
Scheme Performance metrics:
, ( )
, ( )
( )
( )i i
i i
iv R OL v k
ki
v R OL v k
AC v
LRROL v
( )
( )i
i
iv R
iv R
AC v
LRROL v
AC(Vi) is the actual number of layers received by viOL(vi) is the maximum number of layers permitted by maxflow
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0
0. 2
0. 4
0. 6
0. 8
1
LRR1 LRR3 LRR5
ROME OLSNC SLSNC
0
0. 2
0. 4
0. 6
0. 8
1
LRR1 LRR3 LRR5
ROME OLSNC SLSNC
Simulation Results
E1, Flat Scheme E1, Exponential Scheme
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Simulation Results
0
0. 2
0. 4
0. 6
0. 8
1
LRR1 LRR3 LRR5
ROME OLSNC SLSNC
0
0. 2
0. 4
0. 6
0. 8
1
LRR1 LRR3 LRR5
ROME OLSNC SLSNC
E2, Flat Scheme E2, Exponential Scheme
The advantage is more obvious in E1, with Exponential Scheme.
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Simulation Results cont
E=E1
Flat Rate
E=E1,
Exponential
E=E2,
Flat Rate
E=E2,
Exponential
ROME 0.9361 0.9560 0.7276 0.9573
OLSNC 1.0000 1.0000 0.9987 0.9982
SLSNC 1.0000 1.0000 0.9941 0.9923
The comparison of LRR
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Future Works
• In undirected networks
• Distributed Network Coding Scheme • Fairness problem
• Layered P2P Streaming Using Network Coding
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Thank You