Class Presentation"

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A Comparison of Layering and Stream Replication Video Multicast Schemes Taehyun Kim and Mostafa H. Ammar Networking and Telecommunications Group Georgia Institute of Technology Atlanta, Georgia

Transcript of Class Presentation"

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A Comparison of Layering and Stream Replication Video

Multicast Schemes

Taehyun Kim and Mostafa H. AmmarNetworking and Telecommunications Group

Georgia Institute of TechnologyAtlanta, Georgia

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Research Goal

A systematic comparison of video multicasting schemes designed to deal with heterogeneous receivers Replicated streams Cumulative layering Non-cumulative layering

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Stream Replication

Multiple video streamsSame content with different data ratesReceiver subscribes to only one streamExample

DSG (Cheung, Ammar, and Li, 1996) SureStream of RealNetworks

Intelligent streaming of Microsoft

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Replicated Stream Multicast

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Cumulative Layering

1 base layer + enhancement layersBase layer

Independently decoded

Enhancement layer Decoded with lower layers Improve the video quality

Example RLM (McCanne, Jacobson, Vetterli, 1996) LVMR (Li, Paul, and Ammar, 1998) MPEG-2/4, H.263 scalability modes

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Layered Video Multicast

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Layering or Replication?

Common wisdom states: “Layering is better than replication” But it depends on

Layering bandwidth penalty Specifics of encoding Protocol complexity Topological placement of receivers

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Bandwidth Penalty

Information theoretic results R(P, 2) R(P, 1, 2)

Packetization overhead Syntactically independent layering

Picture header GOP information Macroblock information

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Experimental Comparison

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Comparison by DP

J. Kimura, F. A. Tobagi, J. M. Pulido, P. J. Emstad, "Perceived quality and bandwidth characterization of layered MPEG-2 video encoding", Proc. of the SPIE, Boston, MA, Sept. 1999

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Providing a Fair Comparison

Need to insure that each scheme is optimized

Two dimensions Selection of stream/layer rates Assignments of streams/layers to

receivers

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Rate allocation

Cumulative layering Optimal receiver partitioning algorithm

(Yang, Kim, and Lam)

Stream replication Cumulative rate allocation

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Stream assignment

Cumulative layering Assign as many layers as possible

Stream replication Greedy algorithm

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Comparison Methodology

Model of network Topology Available bandwidth Placement of source and receivers

Determine optimal stream rates and allocation

Evaluate performance

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Performance Metrics

Average reception rateTotal bandwidth usageAverage effective reception rate Efficiency

usage bandwidth Totalrate reception effective Total

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Network Topology

GT-ITM Number of server = 1 Number of receivers = 1,640 Number of transit domains = 10

Number of layers = 8Amount of penalty = 25%

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Data reception rate

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Bandwidth usage

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Effective reception rate

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Efficiency

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Effect of overhead

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Effect of the number of layers

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Clustered Distribution

Topology consideration Layering favors clustered receivers Stream replication favors randomly

distributed receiversSimulate when receivers are clustered

within one transit domain

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Effective reception rate

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Protocol Complexity

Layered video multicasting Multiple join for a receiver Large multicast group size

Replicated stream video multicasting One group for a receiver Small multicast group size

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Average group size

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Conclusion

Identified the factors affecting relative merits of layering versus replication Layering penalty Specifics of the encoding Topological placement Protocol complexity

Developed stream assignment and rate allocation algorithm

Investigated the conditions under which each scheme is superior

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Optimal Quality Adaptation for MPEG-4 Fine-Grained

Scalable Video

Taehyun Kim and Mostafa H. AmmarNetworking and Telecommunications Group

Georgia Institute of TechnologyAtlanta, Georgia

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Related Work (1/2)

S. Nelakuditi, et al, “Providing smoother quality layered video stream,” NOSSDAV 2000

Goals Achieving smoother quality for layered

CBR video using receiver buffer Minimizing quality variation (maximizing

runs of continuous frames)

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Algorithm

Forward scan Switching between select and discard

phase Entering select phase if buffer is full Entering discard phase if buffer is empty

Backward scan Exploiting the residual buffer Extending each run

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Bandwidth Model

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Experimental Result

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Experimental Result

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Related Work (2/2)

D. Saparilla, et al, “Optimal streaming of layered video,” INFOCOM 2000

Goal Investigating the bandwidth allocation

problem to minimize loss probability Modeling the source video and the

available bandwidth by stochastic process

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Main Result

Static policy Allocating bandwidth in proportion to

long run average data rate Optimal for infinite length, independent

layeringThreshold-based policy

If the base layer buffer is below a threshold, allocate bandwidth to the base layer

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Research Goal of MPEG4 FGS Quality Adaptation

Maximization of the perceptual video quality by minimizing quality variation

Accommodation of the mismatch between Rate variability of VBR video Available bandwidth variability

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MPEG4 FGS Hybrid Scalability

Base layerEnhancement layer

FGS layer: improving video quality FGST layer: improving temporal

resolution

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Rate Variability

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Quality Adaptation Framework

d

Ci[k]

Si[k]

time

cum

ulat

ive

data

in th

e ith

laye

r Xi[k]

k1 k2k0

select selectdiscard

C[k]: transmission resource constraintX[k]: cumulative data sizeS[k]: cumulative selected data sized: threshold

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Optimal Quality Adaptation

Threshold should be equal to the receiver buffer size to achieve Minimum quality variability Necessary condition of maximum

bandwidth utilization

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Online Adaptation

Estimating the threshold point without assuming the available bandwidth information in advance

The available bandwidth is estimated by an MA style linear estimator

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Experiment Model

0

6

2

4

7

3

5

TFRC sender TFRC receiver

1

TCP sender TCP receiver

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Bandwidth Variability

TCPTFRC

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Performance over TFRC

Threshold-based streaming (Infocom’00)

Online adaptation

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Performance over TCP

Threshold-based streaming

Online adaptation

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Conclusion

Accommodated the mismatch between the rate variability and the bandwidth variability

Developed an optimal quality adaptation scheme for MPEG4 FGS video to reduce quality variation

Investigated the perceptual quality of different algorithms and options