Traffic grooming in WDM mesh networks with guaranteed survivability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Traffic grooming techniques in optical networks are attracting increasing research attention in order to handle the huge bandwidth mismatch between high capacity lightpaths and low-rate individual traffic requests. It is important to have guaranteed survivability of all user connections in such networks. Path protection has emerged as a widely accepted technique for survivable WDM network design. However, it requires allocating resources for backup lightpaths, which remain idle under normal fault-free conditions. In this paper, we introduce a new design strategy for survivable traffic grooming in WDM networks, under specified resource constraints. Our approach addresses the complete design problem including logical topology design, RWA, and routing of (subwavelength) requests over the logical topology. We further ensure that the resultant logical topology is able to handle the entire traffic request after any single link failure. We first present two ILP formulations for optimally designing a survivable logical topology, and then propose a heuristic for larger networks. Experimental results demonstrate that this new approach is able to provide guaranteed bandwidth, and is much more efficient in terms of resource utilization, compared to both dedicated and shared path protection.
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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 it