Channel-Based RSA Approaches for QoS Protection of Slices Over Elastic Optical Networks
Bibliographic record
Abstract
Resource efficiency and survivability are critical concerns in elastic optical networks (EONs) with virtualization. In this paper, we investigate some important aspects in network survivability design against single-link failure under dedicated protection and bandwidth squeezing schemes when multiple virtual topologies are employed. We propose a link-path integer linear programming (ILP) formulation to solve the joint virtualization and survivability problem in elastic optical networks for large network instances, and derive some different types of protection for each virtual topology considering a channel-based spectrum approach to solve the spectrum allocation. Besides, we propose a heuristic to find a pair of predefined paths to ILP formulation aiming to minimize the link load. The proposed ILP and heuristic provide effective survivability solutions and spectrum resource savings for a cooperative design of modern survivable virtualized EONs taking advantages of a link-path model.
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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".