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VBR Video Traffic Models [Kõva köide]

(North Carolina State University, Raleigh, North Carolina),
  • Formaat: Hardback, 148 pages, kõrgus x laius x paksus: 242x163x20 mm, kaal: 422 g
  • Ilmumisaeg: 28-Mar-2014
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 184821636X
  • ISBN-13: 9781848216365
Teised raamatud teemal:
VBR Video Traffic ModelsSuurem pilt
  • Formaat: Hardback, 148 pages, kõrgus x laius x paksus: 242x163x20 mm, kaal: 422 g
  • Ilmumisaeg: 28-Mar-2014
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 184821636X
  • ISBN-13: 9781848216365
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781848216365.html
Märksõnad:
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.
Introduction vii
Chapter 1 Video Coding
1(18)
1.1 Video coding
1(2)
1.2 Video coding standards
3(12)
1.2.1 The MPEG video coding standard
4(4)
1.2.2 H.264/MPEG-4 AVC
8(2)
1.2.3 H.264 SVC
10(2)
1.2.4 H.264 MVC
12(3)
1.3 Rate control
15(1)
1.4 Summary
16(3)
Chapter 2 Video Traffic Modeling
19(46)
2.1 The AR models
19(13)
2.1.1 Review of the AR process
20(2)
2.1.2 Survey of AR video traffic models
22(10)
2.2 Models based on Markov processes
32(11)
2.2.1 Review of Markov process models
33(2)
2.2.2 Survey of Markov process models
35(7)
2.2.3 Summary
42(1)
2.3 Self-similar models
43(4)
2.3.1 A survey of self-similar models for video traffic
44(2)
2.3.2 Summary
46(1)
2.4 Wavelet-based models
47(3)
2.4.1 Survey of wavelet-based video traffic models
47(2)
2.4.2 Summary
49(1)
2.5 Other approaches
50(4)
2.5.1 The M/G/∞ process
50(1)
2.5.2 The SARIMA model
51(2)
2.5.3 TES-based models
53(1)
2.5.4 Summary
54(1)
2.6 Video traffic models for layered scalable video
54(4)
2.6.1 Summary
57(1)
2.7 Video traffic models for three-dimensional video
58(4)
2.7.1 A video traffic model for MVC video
60(2)
2.8 Conclusion
62(3)
Chapter 3 Evaluation of Video Traffic Models for H.264 AVC VIDEO
65(32)
3.1 Model implementation
67(6)
3.1.1 The DAR(1) model
67(2)
3.1.2 A frame-based AR(2) model
69(1)
3.1.3 A Markov-modulated gamma model
70(2)
3.1.4 A wavelet model
72(1)
3.2 Experimental setup
73(1)
3.3 Frame size distribution and ACF comparisons
74(7)
3.4 QoS evaluation
81(13)
3.4.1 End-to-end delay
81(1)
3.4.2 Jitter
82(1)
3.4.3 Packet loss
83(1)
3.4.4 The simulation model
84(2)
3.4.5 Results
86(8)
3.5 Conclusion
94(3)
Chapter 4 Evaluation of Video Traffic Model for H.264 MVC Video
97(18)
4.1 A video traffic model for MVC video
97(2)
4.2 Experimental setup
99(1)
4.3 Results
100(13)
4.3.1 Q--Q plots and ACF comparisons
100(1)
4.3.2 QoS evaluation
100(13)
4.4 Conclusion
113(2)
Conclusion 115(4)
Appendix 119(12)
Glossary 131(4)
Bibliography 135(10)
Index 145
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.