Fairness control in wavelength-routed WDM ring networks
Why this work is in the frame
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Bibliographic record
Abstract
We investigate a threshold-based wavelength allocation scheme in order to support fairness and service differentiation in WDM unidirectional ring networks. A ring network can handle different classes of traffic streams, which differ by their hop-counts (i.e., the number of hops used from source to destination). We assume that for each class of traffic, call interarrival and holding times are exponentially distributed. In such a network, classes of calls with smaller hop-counts, experience lower blocking rates than ones with greater hop-counts. In this paper, a multi-threshold wavelength allocation scheme is proposed to provide equal blocking probabilities experienced by different classes. A recursive simulation-based algorithm is designed to numerically compute the optimal thresholds. Simulation results compare the performance of our proposed scheme, with that of complete sharing and complete partitioning schemes
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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