a comparison of layering and stream replication video multicast schemes
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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. Research Goal. - PowerPoint PPT PresentationTRANSCRIPT
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