Distributed Holding-Time-Aware shared-path-protection provisioning framework for optical networks
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Bibliographic record
Abstract
New applications are likely to ask for a more flexible bandwidth, large bandwidth for limited amount of time. In order to meet these new requirements, flexible optical transport networks in which connections could be set up and released on dynamic short-term basis have to be introduced. We propose a distributed Holding-Time-Aware provisioning framework based on intelligent destination routing to assign and manage the working and the protection paths as well as their wavelength(s) of each connection. In our framework, we propose to utilize knowledge of connection holding time to provide efficient provisioning of shared-path-protected connections in survivable optical mesh networks. We show through a simulation study that the performance of the proposed holding-time-aware compared to a holding-time-unaware is significant.
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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 | 0.001 |
| 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