Delay Analysis and Routing for Two-Dimensional VANETs Using Carry-and-Forward Mechanism
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Bibliographic record
Abstract
For disconnected Vehicular Ad hoc NETworks (VANETs), the carry-and-forward mechanism is promising to ensure the delivery success ratio at the cost of a longer delay, as the vehicle travel speed is much lower than the wireless signal propagation speed. Estimating delay is critical to select the paths with low delay, and is also challenging given the random topology and high mobility, and the difficulty to let the message propagate along the selected path. In this paper, we first propose a simple yet effective propagation strategy considering bidirectional vehicle traffic for two-dimensional VANETs, so the opposite-direction vehicles can be used to accelerate the message propagation and the message can largely follow the selected path. Focusing on the propagation delay, an analytical framework is developed to quantify the expected path delay. Using the analytical model, a source node can apply the shortest-path algorithm to select the path with the lowest expected delay. Performance evaluation by simulation show that, when the vehicle density is uneven but known, the proposed Minimum Delay Routing Algorithm can achieve a substantial reduction in delay compared with the geocast-routing approach, and its performance is close to the flooding-based Epidemic algorithm, while our solution maintains only a single copy of the message.
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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 | 0.000 | 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