Broadcasting Video Streams Encoded With Arbitrary Bit Rates in Energy-Constrained Mobile TV Networks
Why this work is in the frame
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Bibliographic record
Abstract
Mobile TV broadcast networks have received significant attention from the industry and academia, as they have already been deployed in several countries around the world and their expected market potential is huge. In such networks, a base station broadcasts TV channels in bursts with bit rates much higher than the encoding bit rates of the videos. This enables mobile receivers to receive a burst of traffic and then turn off their receiving circuits till the next burst to conserve energy. The base station needs to construct a transmission schedule for all bursts of different TV channels. Constructing optimal (in terms of energy saving) transmission schedules has been shown to be an NP-complete problem when the TV channels carry video streams encoded at arbitrary and variable bit rates. In this paper, we propose a near-optimal approximation algorithm to solve this problem. We prove the correctness of the proposed algorithm and derive its approximation factor. We also conduct extensive evaluation of our algorithm using implementation in a real mobile TV testbed as well as simulations. Our experimental and simulation results show that the proposed algorithm: 1) is practical and produces correct burst schedules; 2) achieves near-optimal energy saving for mobile devices; and 3) runs efficiently in real time and scales to large scheduling problems.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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