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| Content Provider | ACM Digital Library |
|---|---|
| Author | Tripathi, Satish K. Krunz, Marwan |
| Abstract | We present a comprehensive model for variable-bit-rate MPEG video streams. This model captures the bit-rate variations at multiple time scales. Long-term variations are captured by incorporating scene changes, which are most noticeable in the fluctuations of I frames. The size of an I frame is modeled by the sum of two random components: a scene-related component and an AR(2) component that accounts for the fluctuations within a scene. Two random processes of i.i.d. rvs are used to model the sizes of P and B frames, respectively. The complete model is then obtained by intermixing the three sub-models according to a given GOP pattern. It is shown that the composite model exhibits long-range dependence (LRD) in the sense that its autocorrelation function is non-summable. The LRD behavior is caused by the repetitive GOP pattern which induces periodic cross-correlations between different types of frames. Using standard statistical methods, we successfully fit our model to several empirical video traces. We then study the queueing performance for video traffic at a statistical multiplexer. The results show that the model is sufficiently accurate in predicting the queueing performance for real video streams. |
| Starting Page | 192 |
| Ending Page | 202 |
| Page Count | 11 |
| File Format | |
| ISBN | 0897919092 |
| DOI | 10.1145/258612.258688 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1997-06-01 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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