Dynamic Constrained Multicast Routing in WDM Networks: Blocking Probability, QoS and Traffic Engineering
Bibliographic record
Abstract
The development of bandwidth-demanding IP multicast applications has made supporting multicasting in optical layer a favorite option. This article examines the dynamic behavior of optical layer multicasting in sparse splitting WDM networks. We proposed a routing algorithm incorporating the Member-only and shortest-widest approaches to achieve the objectives of Quality of Service (QoS) and traffic engineering in dynamic environment, assuming reasonable blocking probability. A Bottle-neck First-Fit wavelength assignment approach was introduced and applied. The study compared the simulation results of the proposed algorithm to that from the shortest-path based Member-only approach. It showed that the proposed algorithm balances traffic loads well, and accommodates more connection requests in low and medium loads. We further investigated the effects of limiting wavelength usage for each forest on overall blocking probability. Moreover, we formally proved that the algorithm can be easily extended to meet the bandwidth requirement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".