A Hybrid Transmission Approach for DASH over MBMS in LTE Network
Why this work is in the frame
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Bibliographic record
Abstract
Dynamic adaptive streaming over HTTP (DASH) has been a research hotspot, and the current studies focus on the DASH transmission optimization using unicast mode. However, DASH streaming also could be transmitted by multicast mode, which could effectively reduce transmission resource consumption especially when multiple DASH clients request the same video program in parallel. In this paper, we propose the Hybrid Transmission strategies for DASH (HTD) in LTE network, which is considered both unicast and multicast modes for DASH. The optimization problem is formulated as a Mixed Binary Integer Programming (MBIP) problem, and a two-level greedy algorithm is proposed, which could improve the quality of experience (QoE) of wireless DASH users, and save the wireless resources in LTE network. Simulation results demonstrate that our scheme achieves better performance than traditional single transmission mode in the literature.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| 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