Differentiated Reliable Routing in Hybrid Vehicular Ad-Hoc Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In hybrid vehicular ad hoc networks (VANETs), roadside units (RSUs) are more powerful and robust than onboard units (OBUs) equipped on vehicles, which can exchange information and synchronize with other RSUs quickly. Due to the fast mobility of vehicles, wireless links in VANETs are particularly vulnerable to failure. Therefore, it is necessary to provide redundancy in terms of provision multiple link-disjoint paths between source and destination. In addition, VANETs support multiple applications, such as road safety applications and commercial applications, which may require different reliabilities. Accordingly, it is important to discover different number of link-disjoint paths for different applications. In this paper, we propose two notions, virtual equivalent node and differentiated reliable path, and develop an on-demand differentiated reliable routing (DRR) protocol for hybrid VANETs. Extensive simulations show that DRR is beneficial to reduce blocking probability and to maintain lower control overhead while providing differentiated services.
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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 | 0.001 |
| 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