Congestion control in signalling free hybrid ATM/CDMA satellite network
Bibliographic record
Abstract
We pursue a performance analysis for computing the various performance criteria in a hybrid time division/asynchronous transfer mode/code division multiple access network, i.e. TDMA/ATM/CDMA network. Users accessing this TDMA/ATM/CDMA uplink frame are assumed to belong to one of 4 service classes, namely video, voice, file and interactive data. Each user accesses only a portion of the subframe slots assigned to its class. A variable frame boundary strategy is used to adjust the subframe boundaries depending on the call load. To alleviate congestion in the assumed hubless signalling free satellite network, the satellite measures the uplink traffic of each class and issues pilot congestion control indicators to on-going calls of each class. These will be subsequently used by ground users to control their activities and police their calls using modified versions of leaky bucket and virtual leaky bucket congestion control techniques. The new techniques alleviate many of difficulties of specific slot assignment, onboard call management, superframe counting and management involved in the state of the art TDMA based systems, and yield a call establishment free yet dynamic and very well controlled access technique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".