Performance Evaluation of Dynamic Restoration Techniques for Survivable Optical Networks
Bibliographic record
Abstract
Applications and users require different recovery services. Some applications are delay sensitive and demand fast restoration, while others are data sensitive and require 100% data recovery. Dynamic restoration techniques, on the other hand, have exclusive restoration abilities in terms of latency, restoration throughput, and complexity. It is therefore important to comprehend the diversity among dynamic restoration techniques in order to effectively mesh their aptitudes to applications requirements. Accordingly, in this paper we evaluate distinct types of dynamic restoration approaches, namely disjoint path, partially joint path, and link restoration to identify their specialty and deficiency in terms of blocking probability, restoration delay, and computational complexity. Our results reveal that partially joint path restoration always obtains the lowest blocking probability. Nevertheless, this scheme has the highest computational complexity. Link restoration is the fastest if fast fault localization is achieved ahead of the restoration process. Conversely, disjoint path restoration always has the highest average restoration delay. However, this approach is the simplest and obtains the lowest computational complexity.
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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".