Protecting a MPLS multicast session tree with bounded switchover time
Bibliographic record
Abstract
This paper proposes an algorithm to protect a Multiprotocol Label Switching (MPLS) multicast tree from a single link failure with bounded switchover time. Existing protecting algorithms include link protection, path protection, dual tree protection, and redundant tree protection. The problems with these algorithms are that they either provide an unbounded switchover time—meaning that in the case of a link failure, the time it takes for the algorithm to discover and switch the traffic over to a backup path is not predictable—or the bandwidth required for such protection is high. The proposed algorithm provides a guaranteed bounded switchover time, while making efficient use of the protection resources. The switchover time for the proposed algorithm is not fixed, but it gives the network administrator greater flexibility, according to the requirements from the MPLS multicast session as well as the availability of the network resources. An easy-to-use network topology builder and a simulator were implemented for the approach. Simulation results demonstrate that the proposed backup path approach with bandwidth optimization significantly reduces the cost of protection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".