On Network Coding Based Multirate Video Streaming in Directed Networks

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On Network Coding Based Multirate Video Streaming
in Directed Networks

• Chenguang Xu and Yinlong Xu
• University 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 MPEGx
  (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 coding
• Packet level encoding at intermediate nodes
• Decoding at receivers
• The common method of network coding
• Linear Coding
• E.g. 2a3b

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An example -Network Coding
T1
F1
T2
?
S
ab
F2
F3
T3
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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 Allerton05
• 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 a, c Layer2 b, d 2 time units as a
generation
a, b, c, d
?
k1ak2bk3ck4d
m1am2bm3cm4d
layer1
m1am2bm3cm4d
k1ak2bk3ck4d
layer1
Streaming
Conventional Content Distribution
For T1 and T2
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Problem Descriptions

• The Model
• Directed Networks G(V,E,c)
• a set of layers Layer 1, Layer 2,Layer k ,
  with a fixed rate rm for layer m
• R is the receivers set
• Objective Maximizing the total layers received

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Basic Assumptions

• Each encoding generation occupying ? 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
• Neednt to pad the shorter packets
  with 0s

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The Coding Scheme- LSNC cont

• The remaining problems
• How to determine the layer for each receiver?
• How to allocate bandwidth for each layer?
• 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.

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OLSNC-An example
By OLSNC, T1 can get 2 layers, and T2 can get 3
layers.
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OLSNC-An example
Without Network Coding
Optimal Multicast Sub-graph T1 2 layers T2 2
layers
Optimal Multicast Tree T1 1 layer T2 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 bandwidth allocated by existed network
  coding algorithm.

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(No Transcript)
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Performance Evaluation

• Simulation Environments
• V v0, v1,v10, Rv1, v2,v10
• Two topologies E1(vi,vj) i lt j ,
  E2((vi,vj) 0 lt j-i 2
• Two layer rate allocation schemes Flat and
  Exponential Scheme
• Performance metrics

AC(Vi) is the actual number of layers received by
vi OL(vi) is the maximum number of layers
permitted by maxflow
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Simulation Results
E1, Exponential Scheme
E1, Flat Scheme
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Simulation Results
E2, Flat Scheme
E2, Exponential Scheme
The advantage is more obvious in E1, with
Exponential Scheme.
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Simulation Results cont
The comparison of LRR
EE1 Flat Rate EE1, Exponential EE2, Flat Rate EE2, 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
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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