Demand-wise shared protection network design with dual-failure restorability
Bibliographic record
Abstract
The availability requirements placed on core communication networks have been rapidly increasing. As the value of the traffic served by these core networks has increased so has the impact of failure. Demand-wise shared protection (DSP) was developed to provide failure survivability in the network that was more efficient than concurrently routing two paths of traffic (1+1 APS), yet was more straightforward to manage than more complex schemes. The DSP model was adapted to ensure, in addition to 100% single failure survivability, a specified minimum level of dual-failure restorability. The effect of enforcing dual-failure restorability in DSP networks was evaluated in terms of cost and overall increases in availability. Counter-intuitively, it was found that in some cases, requiring some specified dual-failure restorability levels can result in decreased availability. DSP was effectively adapted to ensure dual-failure restorability, however, in order to capitalize on the capacity sharing aspects of the model, networks must be sufficiently well connected.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".