Optimal bandwidth allocation with dynamic multi-path routing for non-critical traffic in AFDX networks
Bibliographic record
Abstract
Avionic networks exerting the Avionics Full-Duplex Switched Ethernet (AFDX) protocol utilize a small amount of the bandwidth to transmit critical traffics. As there is an increasing demand on data exchange for non critical applications, it is of great interest to make use of the physically available capability of the network through optimal bandwidth allocation. In this paper, the problem of bandwidth allocation in AFDX networks is treated in the framework of Network Utility Maximization (NUM). In the present work, multi-path routing is used for non-critical applications to explore the available bandwidth and to improve system performance. The optimization problem is decomposed into a rate update subproblem and a traffic routing subproblem linked together by a pricing dynamic system. A distributed algorithm for bandwidth allocation with multi-path routing is developed and the convergence of the algorithm is proven using Lyapunov stability theory. Some issues related to the implementation of the devolved algorithm in the context of real AFDX networks are addressed and the corresponding solutions are provided. Finally, TrueTime based simulations conform the viability and the applicability of the proposed approach.
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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 | 0.000 | 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 | 0.000 |
| 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".