Bibliographic record
Abstract
We consider the routing problem that arises in the design of a virtual logical topology over a wavelength division multiplexed all optical network (AON). The logical topology is created by setting up lightpaths-end-to-end optical channels-created over the AON by suitable optical switching and routing. These lightpaths form the directed arcs of the logical topology. The combined problem of setting up lightpaths and routing of traffic over these lightpaths, in an optimal manner, is called the virtual topology design problem. The problem of designing such a topology and routing traffic over this topology with the objective of minimizing the network congestion while restricting the average propagation delay between source-destination pairs, and the degree of the logical topology, has been considered by Ramaswamy and Sivarajan (1996), and formulated as a large mixed linear integer program (MILP). For a given logical topology, the problem of optimal routing of traffic becomes a large linear program. We show that, by exploiting the special structure of this linear program, the routing problem can be managed and solved much more efficiently.
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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".