There has been a phenomenal growth in video applications over the past few years. An accurate traffic model of Variable Bit Rate (VBR) video is necessary for performance evaluation of a network design and for generating synthetic traffic that can be used for benchmarking a network. A large number of models for VBR video traffic have been proposed in the literature for different types of video in the past 20 years. Here, the authors have classified and surveyed these models and have also evaluated the models for H.264 AVC and MVC encoded video and discussed their findings.
Зміст
INTRODUCTION vii
CHAPTER 1. VIDEO CODING 1
1.1. Video coding 1
1.2. Video coding standards 3
1.2.1. The MPEG video coding standard 4
1.2.2. H.264/MPEG-4 AVC 8
1.2.3. H.264 SVC 10
1.2.4. H.264 MVC 12
1.3. Rate control 15
1.4. Summary 16
CHAPTER 2. VIDEO TRAFFIC MODELING 19
2.1. The AR models 19
2.1.1. Review of the AR process 20
2.1.2. Survey of AR video traffic models 22
2.2. Models based on Markov processes 32
2.2.1. Review of Markov process models 33
2.2.2. Survey of Markov process models 35
2.2.3. Summary 42
2.3. Self-similar models 43
2.3.1. A survey of self-similar models for video traffic 44
2.3.2. Summary 46
2.4. Wavelet-based models 47
2.4.1. Survey of wavelet-based video traffic models 47
2.4.2. Summary 49
2.5. Other approaches 50
2.5.1. The M/G/ infinity process 50
2.5.2. The SARIMA model 51
2.5.3. TES-based models 53
2.5.4. Summary 54
2.6. Video traffic models for layered scalable video 54
2.6.1. Summary 57
2.7. Video traffic models for three-dimensional video 58
2.7.1. A video traffic model for MVC video 60
2.8. Conclusion 62
CHAPTER 3. EVALUATION OF VIDEO TRAFFIC MODELS FOR H.264 AVC VIDEO 65
3.1. Model implementation 67
3.1.1. The DAR(1) model 67
3.1.2. A frame-based AR(2) model 69
3.1.3. A Markov-modulated gamma mode 70
3.1.4. A wavelet model 72
3.2. Experimental setup 73
3.3. Frame size distribution and ACF comparisons 74
3.4. Qo S evaluation 81
3.4.1. End-to-end delay 81
3.4.2. Jitter 82
3.4.3. Packet loss 83
3.4.4. The simulation model 84
3.4.5. Results 86
3.5. Conclusion 94
CHAPTER 4. EVALUATION OF VIDEO TRAFFIC MODEL FOR H.264 MVC VIDEO 97
4.1. A video traffic model for MVC video 97
4.2. Experimental setup 99
4.3. Results 100
4.3.1. Q-Q plots and ACF comparisons 100
4.3.2. Qo S evaluation 100
4.4. Conclusion 113
CONCLUSION 115
APPENDIX 119
GLOSSARY 131
BIBLIOGRAPHY 135
INDEX 145
Про автора
Savera Tanwir, Computer Science Department at North Carolina State University, USA.
Harry Perros is a distinguished Graduate Professor in the Computer Science Department at North Carolina State University, USA.
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