Aggregate flow control: improving assurances for differentiated services network
Why this work is in the frame
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Bibliographic record
Abstract
The differentiated services architecture is a simple, but novel, approach for providing service differentiation in an IP network. However, there are various issues to be addressed before any sophisticated end-to-end services can be offered. This work proposes an aggregate flow control (AFC) technique with a Diffserv traffic conditioner to improve the bandwidth and delay assurance of differentiated services. A prototype has been developed to study the end-to-end behavior of customer aggregates. In particular, this new approach improves performance in the following manner: (1) fairness issues among aggregated customer traffic with different number of micro-flows in an aggregate, interaction of non-responsive traffic (UDP) and responsive traffic (TCP), and the effect of different packet sizes in aggregates; (2) improved transactions per second for short TCP flows; and (3) reduced inter-packet delay variation for streaming UDP traffic. Experiments are also performed in a topology with multiple congestion points to show an improved treatment of conformant aggregates, and the ability of AFC to handle multiple aggregates and differing target rates.
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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 | 0.001 | 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