Effect of ATM networks on the leaky bucket based characterization of IS-IP guaranteed service flows in an IP-ATM internetwork
Bibliographic record
Abstract
This paper addresses the problem of determining the change in the leaky bucket (LB) based characterization of a guaranteed service flow as it traverses an ATM subnet in an IP-ATM internetwork. The LB-characterization of the flow changes at the ATM network boundaries since overhead is added/removed and delay is introduced due to the mapping between IP packets and ATM cells. We obtained analytical results on the change in the LB-characterization by analysing the effect of the ingress AAL5, egress AAL5, and ATM schedulers on the guaranteed service traffic. We verified our analytical results by simulation, using OPNET. Our main contribution is the determination of how the leaky bucket based characterization of a guaranteed service flow changes as it traverses an ATM subnet. These results are very important for resource allocation within the ATM subnet to support end-to-end guaranteed service sessions.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".