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Video Modeling
Pravin Rajamoney
CSE-581 Network Technology
Papers:
• Analysis, Modeling and Generation of Self-Similar VBR Video Traffic. M.W.Garrentt and W.Willinger
• The Correlation Structure for a Class of Scene-Based Video Models and Its Impact on the Dimensioning of Video Buffers. M.M.Krunz and A.M.Ramasamy
• Hurst Parameter Estimation of Long-Range Dependent VBR MPEG Video Traffic in ATM Networks. S.H.Hong, R.Park and C.B.Lee
• Simple and Efficient Models for Variable Bit Rate MPEG Video Traffic. O.Rose
Acronyms
MPEG Moving Pictures Expert Group
VBR Variable Bit Rate
CBR Constant Bit Rate
GOP Group of Pictures
ATM Asynchronous Transfer Mode
SRD Short Range Dependent
LRD Long Range Dependent
MPEG-2 Video Theory
GOP = 12 IBBPBBPBBPBB
I Picture = Intra coded pictures
P Picture = Predictive coded pictures
B Picture = Bi-directionally coded pictures
2 min review on
Field rate2 fields per frame
Frame rate29.97 frames per second (US) NTSC25 frames per second (Europe) PALLess for computers
Spatial encoding
Temporal encoding
MPEG-2 Video Theory
CBR vs. VBR
CBR videoAdvantage:
• Fluid flow video model
• easier buffer management
• easier on the network
Disadvantage:
• Not bandwidth efficiente.g. If average video bandwidth is 1.5Mbps, but its spike are as high
as 3.5Mbps. Network must always guarantee 3.5Mbps
CBR vs. VBR
VBR videoAdvantage:
• Bandwidth efficient
• Bursty
Disadvantage:
• Difficult to model
• Buffer management required
• Data rate control required
Why model VBR video?
• Simulation• Analyze the stream for a particular network.
How do you make sense out of this?
Types of video modeling
• Probability density of Gamma/Pareto model ( modified bell shape)
• Scene-oriented model
• Markov chain model
• Histogram model (0th order Markov chain)
Gamma/Pareto model
Short Range Dependence (SRD)• Short time scale 10ms
• 200 frames
• Markov chain model, ARIMA process
Long Range Dependent (LRD)
• Synonymous for “Hurst effect”
• Also know as “persistence phenomena”
Observation of an empirical record being significantly correlated to observation that are far removed in time
Hurst value: 0.5 - ~0.75 Low activity~0.75 - ~0.9 Medium activity ~0.9 - 1 High activity
Hurst parameter is related to the amount of motion involved in the sequence
Why simulate VBR video?
• Calculate minimum reservation rate. R*• Amount of buffering needed in the system
for it not to overflow
Why simulate VBR video?
BANDWIDTHBitrate Bandwidth utilization
Conclusion• LRD must be taken into consideration when
modeling VBR video• VBR video is content dependent• Bandwidth and buffer size depends on the
video mean bit rate• ATM systems:
Peak rate
Sustain rate
Average VBR rate
• Network characterization, for real-time VBR video.