Global congestion control in hybrid ATM/TDMA networks
Bibliographic record
Abstract
A new global congestion control scheme is analyzed for the ATM multiplexer node. This scheme is based on the leaky bucket and virtual leaky bucket techniques. It prioritizes transit traffic over local traffic. It ensures quality of service (QOS) to several classes of traffic (i.e., video, voice and data, etc.). A new global congestion control algorithm is designed using the congestion criteria of the adjacent nodes. Early warning cells are transmitted periodically to all adjacent nodes to communicate congestion criteria. The transport users are assumed to be generic ATM sources. The transport users modulate end-to-end flow control parameters, i.e., protocol data unit size in case of video and voice users, and window size in case of data users, based on global congestion status. Simple analytical formulas are derived for global congestion criteria, to represent the required bandwidth to support various traffic classes of service.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".