Enhanced pool sharing: a constraint-based routing algorithm for shared mesh restoration networks [Invited]
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
Feature Issue on Next-Generation WDM Network Design and Routing (WDMN). We investigate the availability performance of networks with shared mesh restoration and demonstrate that these networks cannot provide highly available protection services. A major factor in the poor performance of shared mesh restoration is that the resources at backup links are shared among demands. If multiple service-affecting failures occur in the network a multitude of these demands will rush to utilize the spare resources on backup links. These resources are not adequate to serve all of these demands simultaneously. We propose a heuristic routing algorithm that attempts to improve the availability performance of shared mesh restoration. We measure the likelihood that a backup link will not be available to restore a newly arrived demand if or when more than one failure occurs in the network. We adjust the backup bandwidth on that link if the measured likelihood exceeds a preset threshold. As a typical representative, we show that the downtime improves by 7%, 11%, and 18% when the total backup bandwidth in the network is increased by 5%, 10%, and 20%, respectively. These values are obtained through a series of fitting experiments.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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