On the overlay network design problem for the S-PVC connections in ATM networks
Bibliographic record
Abstract
In this paper we tackle the design problem of the trunk group (TG) overlay in wide area ATM networks under reliability constraints. The TGs are composed of virtual paths (VPs) that the soft-permanent virtual connections (S-PVCs) can ride on. The private network-network interface (PNNI) routing standard is used to route these connections. The design problem consists to find the capacity and the administrative weight (AW) of each TG that ensure the successful rerouting of the S-PVCs for all failure scenarios of interest to the network planner. The objective is to minimize the cost of the TG overlay. An optimization model is proposed as well as a tabu search algorithm. A detailed TG overlay design example is performed and tested. The results showed that the tabu-based algorithm has improved the solution by 9.80%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".