doc.: ieee 802.11-09/0709r2 submission july 2009 carlos cordeiro, intelslide 1 lightly compressed...

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July 20 09 Carlo s Cor deiro Slide 1 doc.: IEEE 802.11-09/0709r2 Submission Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: Name Affiliat ions Addre ss Phone Email Carlos Cordeiro Intel Corp. OR, USA 503- 712- 9356 [email protected] m V. Srinivasa Somayazulu Intel Corp. OR, USA V.Srinivasa.Somayazulu@i ntel.com Guoqing Li Intel Corp. OR, USA [email protected]

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Page 1: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 1

doc.: IEEE 802.11-09/0709r2

Submission

Lightly Compressed Video Traffic Modeling

Date: 2009-07-02

Authors:

Name Affiliations Address Phone Email

Carlos Cordeiro Intel Corp. OR, USA 503-712-9356

[email protected]

V. Srinivasa Somayazulu Intel Corp. OR, USA [email protected]

Guoqing Li Intel Corp. OR, USA [email protected]

Page 2: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 2

doc.: IEEE 802.11-09/0709r2

Submission

Objective

• As part of the TGad evaluation methodology described in 802.11/09-296r6, TGad needs to define a model for lightly compressed video

• In this presentation we propose a lightly compressed video traffic model that can be used for TGad proposal evaluation

Page 3: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 3

doc.: IEEE 802.11-09/0709r2

Submission

Introduction

• Traffic modeling is an old discipline, but which remains very challenging

• For the specific case of compressed video traffic, a model has a high dependence on the video source and compression method used

• Here we derive a model based on a publicly available video source and compression standard, and propose that this model be used by TGad– An alternative model would be to use a random distribution, but even in

this case some level of parameter estimation is needed

– We believe such model to be reasonable for the purpose of TGad proposal evaluation

Page 4: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 4

doc.: IEEE 802.11-09/0709r2

Submission

Video compression in 60GHz (1)

• The choice of compression technology to meet 60GHz requirements is still being debated

• However, H.264 is a popular block based compression scheme– Trace data encoded with H.264 is publicly available– Codec algorithm is widely known and reproducible

• Specific restriction on H.264 codec profiles: only intra-frame coding, no P and B frames– B frames introduce unacceptable latency > 1 frame– P and B frames introduce large memory requirements at decoder – this may

be contentious– P and B frames also introduce large error sensitivity: Intra-frame coding is

more robust to transmission errors• Therefore, for H.264-compressed video at 60GHz, we believe it is

more realistic to assume a model whereby only I frames are included

Propose to build a model for compressed video using H.264 I-only encoder

Page 5: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 5

doc.: IEEE 802.11-09/0709r2

Submission

Video compression in 60GHz (2)

• To meet the video requirements in 11-09-0296r6 for operation in 60GHz, we need to use a modeling method that meets the 2ms latency requirement and buffer constraints

• That implies that compression at 60GHz will likely be performed at the slice level

– Slice-based compression is defined in the H.264 standard itself*

– Can define small slice sizes consistent with low latency

– E.g., for 1920x1080p video, a slice size of 16*1920*3bytes ~ 92Kbytes (except for the last slice, which is smaller)

• However, all publicly available compression traces are on a video frame basis

• We need slice-based statistics

1920

1080

16

16

...

Slice 1MB1 MB2

MB = Macro-block

Slice 2

Slice 68

...

1080p Frame

* As an example, Cavium Networks (http://www.caviumnetworks.com/) provides a low-latency H.264 based solution using this feature

Page 6: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 6

doc.: IEEE 802.11-09/0709r2

Submission

Trace-based modeling

• A H.264 standards based codec is used to generate slice-based trace data for the lightly video compression modeling

– Used the existing CAVLC Intra 4:4:4 H.264 profile • Trace data generated from the “Breeze” video clip*

– HD 4:4:4 1280x720 30fps movie– 1280x16 slice (scaled up to 1920x16 and 60 fps for 1080p60)– Intra-frame-only encoding used: all slices are I slices (no rate control)– Compression ratio of ~ 5.8 for an average bit-rate of ~515Mbps for 1080p60 source

Compressed slice statistics

No. of slices 20745

Min/Max/Ave slice size (Kbytes) 6.7 / 21.22 / 15.8

Variance (Kbytes) 1.823

* P. Topiwala, C. Tu, “Introduction to the Viper Dataset,” ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, Doc. #JVT-J039, December 2003

Page 7: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 7

doc.: IEEE 802.11-09/0709r2

Submission

Proposed compressed video model (1)

• We plot the PDF of the actual slice size distribution, and the corresponding Normal distribution obtained using the Method of Moments

• The Normal distribution seems to provide a reasonable approximation to the measured video data– µ = 15.798 Kbytes

– σ = 1.350 Kbytes

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 5 10 15 20 25

Slice size (Kbytes)

PD

F

Slice data Normal(15.798,1.350)

Page 8: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 8

doc.: IEEE 802.11-09/0709r2

Submission

Proposed compressed video model (2)

• The model is based upon one particular video sequence, compressed at one particular bit rate – Therefore, the Normal distribution on the previous slide generates mean bit rates of ~515 Mbps, and a peak

bit rate of 693Mbps

• How to generate slice sizes for different target bit rates ranging up to 3Gbps, while keeping the model simple and avoiding multiple models for different rates?

• Proposal: Scale the mean of the original Normal distribution according to the desired bit rate– But place an upper bound of 92.160 Kbytes on the slice size: size cannot exceed the raw data!

• For example:

Desired avg. bit rate Normal distribution for model

0.4*515 Mbps Normal(0.4*µ, 0.4*σ)

2*515 Mbps Normal(2*µ, 2*σ)

k*515 Mbps Normal(k*µ, k*σ)

… …

Page 9: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 9

doc.: IEEE 802.11-09/0709r2

Submission

Proposed compressed video model (3)

• Parameters– Slice inter-arrival time (IAT) is constant and equal to 1/4080 seconds

• Since the number of slices per second = (60 fps) * (68 slices per frame) = 4080

– Slice sizes generated with a Normal distribution with µ = 15.798 Kbytes and σ = 1.350 Kbytes• Yields avg. bit rate (b) = 515 Mbps, peak = 693 Mbps

• Algorithm– Select target avg. bit rate B, such that B <= 2986 Mbps

– At each IAT, generate a slice size with the following distribution: Normal(µ*(B/b), σ*(B/b))• If slice size > 92.160 Kbytes, set slice size = 92.160 Kbytes

Page 10: Doc.: IEEE 802.11-09/0709r2 Submission July 2009 Carlos Cordeiro, IntelSlide 1 Lightly Compressed Video Traffic Modeling Date: 2009-07-02 Authors: NameAffiliationsAddressPhoneEmail

July 2009

Carlos Cordeiro, Intel

Slide 10

doc.: IEEE 802.11-09/0709r2

Submission

Conclusions

• To meet the stringent latency requirements, compressed video transmission in 60GHz will be done on a slice basis

• A slice-based model has been developed based on publicly available video source and a standards based H.264 codec

• The model uses a Normal distribution, with parameters that can be scaled to match different bit rates– In practice the proposed Normal distribution may or may not be

applicable to other video sources and/or bit rates, but we believe this to be sufficient for TGad purposes

• Therefore, we propose that the proposed slice-based model be used in the TGad lightly compressed video evaluation methodology

• Next steps: define target average bit rates for the simulation scenarios in the evaluation methodology