Survivable WDM Networks Design with Non-Simple p-Cycle-Based PWCE
Bibliographic record
Abstract
We propose a new design approach of survivable WDM networks using simple and non-simple p-cycles-based protected working capacity envelope (PWCE). We investigate the added-value of the non-simple p-cycles over simple p-cycle protection method in terms of capacity efficiency and reliability. As opposed to the prevalent two-step design approach where an explicit enumeration of all/set of p-cycles step is performed ahead of an optimization step, we develop a new optimization approach using a large scale optimization tool named column generation technique, where only few globally optimal cycles are generated dynamically during the optimization process. We conduct performance evaluation experiments on various network topologies, using different metrics in order to measure the added- value of the non-simple p-cycles over simple p-cycles in the design of survivable WDM networks based on PWCE. It is shown that depending on the network topologies, and in particular of their connectivity, significant protection improvement can be achieved when using non simple p-cycles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".