Monitoring Cycle Design for Fast Link Failure Localization in All-Optical Networks
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Bibliographic record
Abstract
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A monitoring cycle (m-cycle) is a preconfigured optical loop-back connection of supervisory wavelengths with a dedicated monitor. In an all-optical network (AON), if a link fails, the supervisory optical signals in a set of m-cycles covering this link will be disrupted. The link failure can be localized using the alarm code generated by the corresponding monitors. In this paper, we first formulate an optimal integer linear program (ILP) for m-cycle design. The objective is to minimize the monitoring cost which consists of the monitor cost and the bandwidth cost (i.e., supervisory wavelength-links). To reduce the ILP running time, a heuristic ILP is also formulated. To the best of our survey, this is the first effort in m-cycle design using ILP, and it leads to two contributions: 1) nonsimple m-cycles are considered; and 2) an efficient tradeoff is allowed between the monitor cost and the bandwidth cost. Numerical results show that our ILP-based approach outperforms the existing m-cycle design algorithms with a significant performance gain. </para>
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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