Dual‐failure restorability analysis of span‐restorable meta‐mesh networks
Bibliographic record
Abstract
Abstract The span‐restorable meta‐mesh model was previously designed as a cutting‐edge technique that enhanced the spare capacity efficiency in low average nodal degree networks. In this technique, lightpaths that fully traverse chains of degree‐2 nodes are provided with a logical express bypass span allowing a distinction between the internal and external working flow capacity that transit the chain. In the event of span failure, lightpaths which would normally traverse the chain in its entirety are allowed to fail back to its anchor nodes such that only the intrachain flow requires allocation of spare capacity. Previous work on the meta‐mesh design considered only single failure restorability. The work herein analyzes dual span failure situations by developing two new integer linear programming models. The first model provides the minimum total cost of designing a meta‐mesh network capable of withstanding dual span failure scenarios. The second model offers a maximization of the dual failure restorability by minimizing the number of nonrestored working capacities with a given limit of total spare capacity investment. Experiments are performed on six master test‐case networks of various topologies and scales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".