A predictive demand assignment multiple access protocol for broadband satellite networks supporting Internet applications
Why this work is in the frame
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Bibliographic record
Abstract
To enhance the performance of broadband satellite networks, the application characteristics should be considered in the design of the medium access control (MAC) protocol. With the rapid expansion of Internet applications and the attractiveness of high speed Internet access via broadband satellite networks, it is important to take into account the self-similar nature of Internet traffic in MAC protocol designs. This paper presents a novel PRedictive Demand Assignment Multiple Access (PRDAMA) protocol for packet communications over broadband satellite networks. PRDAMA allocates bandwidth resources by estimating the positive varying trend of the Internet traffic to facilitate prediction of the resource requirements of the Earth stations. Simulation results demonstrate that PRDAMA achieves a lower delay compared with other DAMA protocols due to its accurate traffic prediction. The influence of different traffic models on the protocol performance is also investigated.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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