Dynamic Routing and Wavelength Assignment in Multifiber WDM Networks with Wavelength Conversion Capability
Bibliographic record
Abstract
This paper proposes a dynamic routing and wavelength assignment (RWA) scheme in multifiber WDM networks with wavelength conversion capability. In multifiber WDM networks, each link consists of multiple fibers. Thus, multiple lightpaths with the same wavelength can be established in the same link as long as they use different fibers. In WDM networks with wavelength conversion, the network nodes have wavelength conversion capability which can convert one wavelength to another. In order to efficiently utilize multifiber and wavelength conversion capability, an appropriate RWA scheme is necessary. The proposed scheme provides RWA for multifiber WDM networks with sparse and full wavelength conversion capability. In the proposed scheme, a route and wavelengths are selected for each lightpath based on wavelength availability and location of nodes with wavelength conversion capability. Through simulation experiments, we show that the proposed scheme reduces the blocking probability of lightpath establishment efficiently.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".