<title>Capacity design studies of span-restorable mesh transport networks with shared-risk link group (SRLG) effects</title>
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
We study the total capacity requirements of span-restorable mesh network designs as the percentage of all possible dual failure combinations incident on a common node is increased. Our interest is in questions such as: Are there any guidelines or insights as to how many such SRLGs can be sustained before the capacity penalty becomes severe? Can we diagnose which SRLGs are the most limiting to overall network efficiency? When would it be worthwhile to take physical measures to eliminate a certain SRLG? In addressing these questions we provide a design formulation and procedure for planning any span-restorable network for a known set of SRLGs. One finding of interest is that if all dual failure combinations incident to a common node are allowed for in the design, then nearly all other dual span failure combinations (any two spans in the network) will also be restorable. We also produce experimental results showing how total capacity depends on the relative number or frequency of co-incident SRLGs and quantify how the type of SRLG will impact design costs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it