Optimal Scheduling and Delay Analysis for AFDX End-Systems
Bibliographic record
Abstract
The present work aims at the reduction of transmission delay at the level of AFDX ES (Avionics Full Duplex Switched Ethernet End-Systems). To this end, two approaches, namely Network Calculus and response time analysis (RTA), are employed in the computation of upper bound delay. To evaluate the delay regarding different scheduling policies, the arrival curve of the flow on output of ES is established for given traffic shaping algorithm and service mode. Computational analysis shows that Bandwidth Allocation Gap (BAG) based scheduling is the optimal policy at the level of AFDX ES, which leads to the tightest output arrival curve among all possible scheduling policies. BAG-based scheduling consists in assigning higher priority to virtual links with smaller BAG thus corresponding to the well known Rate-Monotonic Algorithm. Furthermore, schedulability criterion are established based on RTA. Additionally, delay bound computation indicates that response time analysis provides a tighter delay bound than that obtained by Network Calculus. Numerical simulations are carried out to confirm the validity, the applicability, and the performance of the proposed scheduling scheme.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".