Priority-aware optical shared protection coupled with mutation probability
Bibliographic record
Abstract
The next big challenge for optical network operators is to meet the diverse availability requirements of the various subscribed services through the adoption of appropriate protection strategies. One promising scheme that has been proposed in the open literature and that is presenting itself as a potential approach to dealing with this challenge is the priority-aware protection scheme. However, the priority-aware protection strategy suffers from a major limitation as it privileges the failed high priority connections taking no account of the failed low priority ones. As such, this paper proposes to combine priority-aware shared protection with a parameter called mutation probability thus giving birth to a more effective protection strategy. The mutation probability parameter expresses the likelihood that a low-priority connection be promoted temporarily to a higher priority level during its recovery. The proposed mutation-based protection strategy therefore allows optical operators to improve the availability of their low-priority clients without violating the availability requirements of their high-priority ones. Performance of this novel protection strategy is analyzed in this paper by precisely calculating the connection unavailability that results from its deployment. A computational framework is proposed in this regard to highlight the merit that the mutation-based protection strategy has over the existing priority-aware protection scheme.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".