QoE-aware adaptive bitrate video streaming over mobile networks with caching proxy
Why this work is in the frame
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Bibliographic record
Abstract
As a widely used over-the-top (OTT) video technique, adaptive bitrate video streaming has attracted considerable research attention and efforts. Traditional bitrate adaptation schemes rely on quality of service (QoS) to assess video delivery quality. However, in this paper, we argue that QoS may not accurately reflect the user-perceived video quality, especially in time-varying wireless networks. Instead, we adopt the concept of quality of experience (QoE) and propose a novel caching-based adaptation scheme to improve the overall QoE, which can more comprehensively gauge the subjective user satisfaction of video quality. Experiments show that the proposed method outperforms existing adaptation schemes in terms of QoE in various network scenarios. This observation is mainly attributed to the merits of our scheme in properly leveraging channel bandwidth prediction and proxy-based content prefetching.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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