Design and Dimensioning of Logical Survivable Topologies Against Multiple Failures
Bibliographic record
Abstract
In IP-over-WDM networks, protection can be offered at the optical layer or at the IP layer. Today, it is well acknowledged that synergies need to be developed between the IP and optical layers in order to optimize the resource utilization and to reduce the costs and the energy consumption of future networks. In this paper, we study the design of logical survivable topologies for service recovery against multiple failures, including SRLG—shared risk link group—failures in IP-over-WDM networks. We propose a new optimization model, called surlog_cgilp, based on a column generation path formulation. It is highly scalable and allows the exact solution of several benchmark instances, which have only been solved with the help of heuristics so far. In the numerical experiments, we investigate the dimensioning of the physical links assuming IP restoration against multiple-link failures. We observe that the redundancy ratios (recovery over primary ratios for the bandwidth requirements) that are obtained are similar to the redundancy ratios reported for optical 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".