Investigation of fast reroute mechanisms in an optical testbed environment
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
In this paper, we investigate and evaluate the performance of two fast reroute mechanisms in packet switched core networks. Such mechanisms enable, in the case of a network fault, the fast switchover of protected traffic onto pre-established backup paths within minimal time (typically below 50 ms) to minimize traffic loss. Our research testbed consists of both real and emulated IP/MPLS Label Switching Routers (LSRs). Using empirical tests, we compare the two fast protection mechanisms MPLS Traffic Engineering (TE) Fast Reroute (FRR), and IP FRR to protect MPLS LDP traffic. In our tests, we consider single link failures protected with pre-provisioned backup paths using TE-FRR tunnels, or IP Fast Reroute (IP-FRR) alternate paths. We compare the two techniques in terms of traffic loss and network time convergence obtained by repeating the tests multiple times.
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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 | 0.000 | 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 it