Fault Detection and Localization Scheme for All-Optical Overlaid-Star TDM Networks
Bibliographic record
Abstract
Fault detection and localization is a crucial issue in all-optical networks. Since most commercially-available all-optical space switches are incapable of detecting the loss of optical signals along the data paths between its input ports and output ports, fault localization becomes a challenge for providing service survivability in such networks. This paper proposes a fault detection and localization scheme for an all-optical overlaid-star TDM network. The proposed scheme employs a fault localization technique that identifies the location of a failure by detecting the power loss of optical signals in data and control channels. Two alternatives are proposed. One requires a control channel on each wavelength of a fiber link while the other requires a small data block to be transmitted in each non-allocated data channel. Based on the proposed fault localization technique, a fault advertisement protocol is further presented, which can be incorporated into the signaling protocol used in the network to facilitate the provisioning of static protection or dynamic restoration. The data loss, fault detection time, and connection recovery time are analyzed for the different failure scenarios.
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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".