An optimal and fully explicit rate controller for high-speed networks
Bibliographic record
Abstract
We have designed and investigated a new congestion control scheme, called the OFEX (Optimal and Fully EXplicit) controller. Different from the existing relatively explicit controllers, this new scheme is able to provide not only optimal bandwidth allocation but also fully explicit congestion signal to sources. It overcomes the drawback of the relatively explicit controllers that “bias” the multi-bottlenecked users, and improves their convergence speed and source throughput performance. Furthermore, the OFEX controller design considers a dynamic model by proposing a remedial measure against the unpredictable bandwidth changes in contention-based networks (such as shared Ethernet and IEEE 802.11). Compared with the former works/controllers, such a remedy also effectively reduces the instantaneous queue size in a link, and thus significantly improving the queueing delay and system stability performance. We have evaluated the effectiveness of the OFEX controller in OPNET. The experimental comparison verifies the superiority of the OFEX controller.
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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 | 0.001 |
| Open science | 0.000 | 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".