Design of a meta-mesh of chain subnetworks: enhancing the attractiveness of mesh-restorable WDM networking on low connectivity graphs
Why this work is in the frame
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Bibliographic record
Abstract
We have developed a design refinement to increase the capacity efficiency of span-restorable mesh networks on sparse facility graphs. The new approach views the network as a "meta-mesh of chain subnetworks". This makes the prospect of WDM mesh networking more economically viable than with previous mesh-based designs where the average nodal degree is low. The meta-mesh graph is a homeomorphism of the complete network in which edges are either direct spans or chains of degree-2 nodes. The main advantage is that loop-back-type spare capacity is provided only for the working demands that originate or terminate in a chain and not for the entire flow that crosses a chain. The transiting ("express") flows are entirely mesh-protected within the meta-mesh graph which is of higher average degree and hence efficiency for mesh restoration than the network as a whole. Nodal equipment savings also arise from the grooming of express lightpaths onto the logical chain-bypass span. Only the meta-mesh nodes need optical cross-connect functionality. Other sites use OADMs and/or glassthroughs. The resultant designs comprise a special class of restorable network that is intermediate between pure span restoration and path restoration. Most of the efficiency of path restoration is achieved, but with a span restoration mechanism which is more localized and potentially faster and simpler than path restoration. The concept lends itself to implementation with OADMs having a passive waveband pass-through feature to support the logical chain bypass spans for express lightpaths.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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