Optimized Transcoding Rate Selection and Packet Scheduling for Transmitting Multiple Video Streams O

1
Optimized Transcoding Rate Selection and Packet
Scheduling for Transmitting Multiple Video
Streams Over a Shared Channel
Mark Kalman, Peter van Beek and Bernd Girod
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Overview

• Application DTV over wireless LAN
• Finding Optimal Transcoding Rates
• Effect of Transcoder Control Lag
• Source Pruning and Packet Scheduling
• Distortion Model
• Delay Model
• Experimental results

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Distribution of DTV over WLAN
diagram taken from van Beek, 2004
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Video Streaming Over Shared Channel
Transcoder
Decoder
0
0
Transcoder
Decoder
1
1
Receiver
Transcoder
Decoder
(Multi-Channel)
2
2
Transcoder
Decoder
3
3
Controller
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Video Streaming Over Shared Channel
Transcoder
Decoder
0
0
Transcoder
Decoder
1
1
Receiver
Transcoder
Decoder
(Multi-Channel)
2
2
Transcoder
Decoder
3
3
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Server Divides Channel Time Among Links
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Link Capacities Vary Over Time
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Transcoders Control Source Rate for Each Link
Transcoder
Decoder
0
0
Transcoder
Decoder
1
1
Receiver
Transcoder
Decoder
(Multi-Channel)
2
2
Transcoder
Decoder
3
3
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R-D for H.264 Transcodings of mobile.cif
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Choosing Optimal Transcoding Rates
- Number of streams
- Fraction of channel time devoted to stream m
- Capacity of link m
- Weights the importance of the distortion of
stream m
- Rate-Distortion function for stream ms source
- Transcoded rate of source m
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Closed-Form Solution using Lagrange Multipliers
(1)
Zhu and Setton 2004
Stuhlmueller, Faerber, Link, and Girod 2000
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Closed-Form Solution using Lagrange Multipliers
(2)
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Transcoders Support Discrete Rates
Iterate to find discrete solution
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Simulated Link Capacities
Link 1
Link 0
Link 2
Link 3
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Channel Time Allocations, Sm
Link 0
Link 1
Link 3
Link 2
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Transcoded Rate
Link 1
Link 0
Link 3
Link 2
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Link 2 Capacity, Sm, Rm - Group Shot
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Backlog of Transmission Queues
Transcoder
Decoder
0
0
Transcoder
Decoder
1
1
Receiver
Transcoder
Decoder
(Multi-Channel)
2
2
Transcoder
Decoder
3
3
Controller
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Backlog of Transmission Queues
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Effect of Transcoder Control Lag (1)
Capacity High
Transcoder
3
Controller
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Effect of Transcoder Control Lag (2)
Capacity Drops!
Transcoder
3
Controller
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Effect of Transcoder Control Lag (3)
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Transcoded Rate
Link 1
Link 0
Link 3
Link 2
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No Lag Y-PSNR 35 dB
66 ms Lag Y-PSNR 27 dB
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Backlog of Transmission Queues
Transcoder
Decoder
0
0
Transcoder
Decoder
1
1
Receiver
Transcoder
Decoder
(Multi-Channel)
2
2
Transcoder
Decoder
3
3
Controller
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Pruning and Scheduling
B
I
B
B
B
P
B
B
B
P
B
B
B
P
Goal Choose packets for dropping that will
approximately maximize expected PSNR
B
P
B
B
P
B
B
I
B
P
Controller
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PSNR Vs. Frame Omission Pattern
B
B
B
B
P
I
P
B
B
B
B
P
P
B
B
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Calculate Probability Of Frame Loss
- Frame arrival deadline
- Number of successful packet transmissions
needed to complete a frame
- Time until timeout
- R.V. modeling the number of timeouts until n
successes if failure (time out) probability is e
(Neg. Binomial Distributed)
- Fraction of channel time devoted to stream m
- R.V. modeling time to complete packet
transmission (Exp. distributed)
- Bernoulli probability that packet transmission
times out
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Calculating Estimated PSNR
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Scheduling Algorithm
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Testing Trace Collection Accuracy
802.11b
media packet
Wired Ethernet
Trace client
Trace server
Synch packets
If wireless channel is in bad state, sends on
wired link are delayed. We dont know if delays
are due to wireless channel or due to timing
inaccuracy
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Flooding with Orinoco 11mbps cards

• Stations separated by 15 meters
• Media packets transmitted continually
• Delay spikes of 15 20 ms seen maybe on a 10-15
  second basis

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Detail of Flooding Trace
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Relative Frequencies of Xm,i
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Relative Frequencies of Delays
Gamma approximation has min KS distance DKS
0.0891
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Pruning Performance
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Scheduling And Transcoder Lag
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Scheduling 66 ms lag Y-PSNR 34 dB
Round-Robin 66 ms lag Y-PSNR 27 dB
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Conclusion

• Closed-Form solution for optimal rates
• Transcoder control lag leads to distortion
• Optimized pruning and packet scheduling
• Simple additive distortion model (No DAG)
• Sum of Packet Delays Modeled as G or Gaussian
• Pruning Performance approaches R-D Optimal
• Scheduling yields over 6 dB gain in simulations