<title>Mesh-restorable networks with complete dual failure restorability and with selectively enhanced dual-failure restorability properties</title>
Why this work is in the frame
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Bibliographic record
Abstract
We consider extensions of the most common mesh-restorable network capacity design formulation that enhance the dual-failure restorability of the designs. A significant finding is that while design for complete dual-failure restorability can require triple the spare capacity, dual failure restorability can be provided for a fairly large set of priority paths with little or no more spare capacity than required for single-failure restorability. As a reference case we first study the capacity needs under complete dual-failure restorability. This shows extremely high capacity penalties to support 100% dual-failure restorability. A second design model allows a user to specify a total capacity budget limit and obtain the highest average dual-failure restorability possible for that investment limit. A third design strategy supports multiple-restorability service class definitions at minimum total cost. Restorability can range from best-efforts-only on any failure to an assurance of complete single and dual-failure restorability, on a per-demand basis. This work shows how to economically support an added service class in the upward quality direction: assured dual failure survivability. This lets a network operator tailor the investment in capacity to provide ultra-high availability on a selective basis, while avoiding the very high investment required for complete dual-failure restorability for all.
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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