An Architecture for Hierarchical Software-Defined Vehicular Networks
Why this work is in the frame
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Bibliographic record
Abstract
With the recent advances in the telecommunications and auto industries, we have witnessed growing interest in ITS, of which VANETs are an essential component. SDN can bring advantages to ITS through its ability to provide flexibility and programmability to networks through a logically centralized controller entity that has a comprehensive view of the network. However, as the SDN paradigm initially had fixed networks in mind, adapting it to work on VANETs requires some changes to address particular characteristics of this kind of scenario, such as the high mobility of its nodes. There has been initial work on bringing SDN concepts to vehicular networks to expand its abilities to provide applications and services through the increased flexibility, but most of these studies do not directly tackle the issue of loss of connectivity with said controller entity. In this article, we propose a hierarchical SDN-based vehicular architecture that aims to have improved performance in the situation of loss of connection with the central SDN controller. Simulation results show that our proposal outperforms traditional routing protocols in the scenario where there is no coordination from the central SDN controller.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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