Recovery from control plane failures in GMPLS‐controlled optical networks
Bibliographic record
Abstract
Abstract The health status of the control plane and the data plane of a GMPLS‐controlled optical network is independent in the physically separated control network implementation. In most control plane designs, besides the topology information, the entities of the routing protocol only record the number of available wavelengths on each link. However, the status of each wavelength is maintained by the entities of the signalling protocol. Without recovery ability of the signalling protocol CR‐LDP, a failure in the control plane will result in the permanent loss of the status information of wavelengths. A mechanism to recover the status information of the wavelengths is proposed. A downstream node maintains a label information database (LID) about assignable (free) labels in each incoming link. A copy of LID is redundantly stored in the upstream node as a label information mirror (LIM). A systematic procedure is proposed to synchronize the contents of a LIM and the corresponding LID. The initialization of a new LDP session with the enhanced recovery mechanism will guarantee the revival of the status information of wavelengths. It can recover multiple control channel failures, but it only applies to single node failure among any pair of adjacent nodes. © Crown copyright 2002. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".