A Study of Fast Flexible Bandwidth Assignment Methods and their Blocking Probabilities for Metro Agile All-optical Ring Networks
Bibliographic record
Abstract
In emerging agile all-optical networks, the time division multiplexing technique in the optical domain is implemented on top of wavelength-division multiplexing to increase channel utilization and to support dynamic bandwidth demands. However, the corresponding dynamic routing, wavelength and timeslot assignment (RWTA) problem has not yet been well addressed with respect to appropriately handling the bandwidth availability. In this paper, we consider a ring topology and apply local-information-based distributed schemes to accommodate fast dynamic bandwidth requests in order to enhance network survivability and to decrease the degree of coordination among nodes. We propose an analytical model to iteratively compute blocking performance of single-fibre networks and present RWTA algorithms for multi-fibre networks based on an indexed fibre designation scheme in order to enhance network blocking performance in all-optical metro networks. A systematic study of the possible combinations of algorithms has been performed, which showed not only that packed algorithms reduce blocking probability, but also that our indexed fibre designation scheme enhances performance.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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".