A directory enabled solution for MPλS path protection and restoration
Bibliographic record
Abstract
It is very important that the large amount of traffic carried by optical channels is protected against potential failures in the network. The MP/spl lambda/S recovery approaches can be classified as local recovery or global recovery. In case of local recovery, the switch over to recovery path is performed by the O-LSR that is immediately upstream of the point of failure, whereas in case of global recovery, the switch over is performed by a predetermined O-LSR known as the O-protection switch LSR (O-PSL). The failure notification plays an important role in the global recovery approach, as the O-PSL has to be notified about the failure in order for the recovery procedure to be initiated. This paper proposes the use of a directory service as part of the global MP/spl lambda/S recovery framework. The proposed architecture enables fast and effective notification of MP/spl lambda/S O-LSP failures, which facilitates quick recovery to the backup O-LSPs. The proposed architecture also scales effectively to all O-LSPs affected by the failure and promotes improved utilization of network resources by greatly reducing the involvement of the O-LSRs in MP/spl lambda/S path protection and restoration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".