Cluster-based smoothing for MPEG-based video-on-demand systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a new technique called cluster-based smoothing to reduce the average per-stream effective bandwidth for the transmission of MPEG compressed video streams. By rearranging the transmission order of frames within windows, the technique exploits the periodic structure of an MPEG video stream, and the bit rate fluctuations across scenes. Trace-driven simulation with empirical MPEG video traces is used to demonstrate the performance advantages of the new technique. The results show that clustering based on frame types in an MPEG video can significantly reduce the per-stream effective bandwidth, particularly when clustering is combined with a modest level of inter-frame smoothing at the VOD source. The buffering and delay requirements associated with cluster-based smoothing are also quantified, and found to be reasonable.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it