BGP with an adaptive minimal route advertisement interval
Bibliographic record
Abstract
The duration of the Minimal Route Advertisement Interval (MRA.1) and the implementation of MRAI timers have a significant influence on the convergence time of the Border Gateway Protocol (BGP). Previous studies have reported existence: of optimal MRAI values that minimize the BGP convergence time for various network topologies and traffic loads. In this thesis, we propose the adaptive MRAI algorithm for adaptive adjustment of MRAI values. We also introduce reusable MRAI timers that limit the number of advertisements for each destination.. The modified BGP is namedl BGP with adaptive MRAI (BGP-AM). BGP-AM perfimnance is evaluated using the BGP processing delay based on reported measurements. ns-2 simulation results d-emonstrate that BGP-AM leads to a shorter convergence time and a number of update messages comparable to the current BGP. Furthermore, BGP-AM convergence time depends linearly on the BGP processing delay.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".