Ingress failure recovery mechanisms in MPLS network
Bibliographic record
Abstract
With the diversification of the traffic carried on the Internet, improvement of QoS has become very demanding in order to realize large capacity, high speed and reliable communication in IP networks. Various models have been proposed to address this need, MPLS being one of the main architectures, having the broadest deployment on the Internet to achieve these QoS goals. It is expected that, in the future, congestion and faults on a label switched path (LSP) will seriously affect service contents, and recovery and restoration of such LSPs would be required to realize a fault-tolerant MPLS network. In this context, researchers in the past have addressed the need with respect to intermediate link and/or node failures. Our main concern is to provide the solution for an ingress label edge router (LER) failure, as this is the node at the very first stage of the LSP. We consider both partial ingress LER failure where only the control plane of the ingress node fails, and total ingress failure resulting in node replacement. Intermediate link and/or node failure is reviewed in the context of ingress LER failures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".