An analytical model for predicting the locations and frequencies of 3R regenerations in all-optical wavelength-routed WDM networks
Why this work is in the frame
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Bibliographic record
Abstract
In all-optical wavelength-switched WDM networks, 3R regeneration does not need to be performed at every node in a path. Thus, a significant cost savings can be realized by efficiently provisioning a limited amount of 3R regeneration resources in each node in the network and utilizing these resources efficiently. In order to aid in these two tasks, we present an analytical model to predict the location and relative frequency of 3R regeneration requests in the network. Because the model is based solely on the topological information of the network, the predictions provided are very general and are independent of specific network operating parameters, such as the routing protocol employed. Simulation results are also presented to verify the accuracy of the model.
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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) | 0.000 | 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 | 0.000 | 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 it