A Comparison of Layering and Stream Replication Video

Multicast Schemes

Taehyun Kim and Mostafa H. AmmarNetworking and Telecommunications Group

Georgia Institute of TechnologyAtlanta, Georgia

Research Goal

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

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

Replicated Stream Multicast

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

Layered Video Multicast

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

Bandwidth Penalty

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

Packetization overhead Syntactically independent layering

Picture header GOP information Macroblock information

Experimental Comparison

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

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

Rate allocation

Cumulative layering Optimal receiver partitioning algorithm

(Yang, Kim, and Lam)

Stream replication Cumulative rate allocation

Stream assignment

Cumulative layering Assign as many layers as possible

Stream replication Greedy algorithm

Comparison Methodology

Model of network Topology Available bandwidth Placement of source and receivers

Determine optimal stream rates and allocation

Evaluate performance

Performance Metrics

Average reception rateTotal bandwidth usageAverage effective reception rate Efficiency

usage bandwidth Totalrate reception effective Total

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%

Data reception rate

Bandwidth usage

Effective reception rate

Efficiency

Effect of overhead

Effect of the number of layers

Clustered Distribution

Topology consideration Layering favors clustered receivers Stream replication favors randomly

distributed receiversSimulate when receivers are clustered

within one transit domain

Effective reception rate

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

Average group size

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

Optimal Quality Adaptation for MPEG-4 Fine-Grained

Scalable Video

Taehyun Kim and Mostafa H. AmmarNetworking and Telecommunications Group

Georgia Institute of TechnologyAtlanta, Georgia

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)

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

Bandwidth Model

Experimental Result

Experimental Result

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

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

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

MPEG4 FGS Hybrid Scalability

Base layerEnhancement layer

FGS layer: improving video quality FGST layer: improving temporal

resolution

Rate Variability

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

Optimal Quality Adaptation

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

bandwidth utilization

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

Experiment Model

0

6

2

4

7

3

5

TFRC sender TFRC receiver

1

TCP sender TCP receiver

Bandwidth Variability

TCPTFRC

Performance over TFRC

Threshold-based streaming (Infocom’00)

Online adaptation

Performance over TCP

Threshold-based streaming

Online adaptation

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