Bibliographic record
Abstract
We present a multi-constrained routing algorithm, called delay-constrained pool sharing (DPS), in a survivable mesh network. The goal of this algorithm is to find a pair of link- disjoint primary and backup paths between a given source and destination nodes, which guarantees full recovery from any single link failure in the network. Our objective is to minimize the resources (such as backup bandwidth) used in the network as well as the total end-to-end delay time along the primary and backup paths. Our approach improves the end-to-end delay performance of the simple pool sharing (SPS) algorithm introduced in the literature, and proposes an integrated approach for quality of service (QoS) and resiliency. Using simulation, we studied the DPS algorithm on the existing North-American transport networks, and showed its improvements compared to the SPS scheme. We also introduce a hybrid algorithm which relaxes the delay constraint on the backup path in favor of maximizing the reusability (sharing) of the backup bandwidth.
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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".