Cooperative Downloading by Multivehicles in Urban VANET
Why this work is in the frame
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Bibliographic record
Abstract
In VANET (vehicular ad hoc network), RSUs (road side units) have limited coverage and high deployment cost, so they are deployed sparsely in urban area, which leads to blind zone (BZ) between adjacent RSUs, where vehicles cannot connect to Internet by RSUs. In this paper, we study how to use RSUs and vehicles to download big files cooperatively in BZ. In order to choose the cooperative vehicles with minimum total delay, we propose a sequential decision vehicle selection method based on the residual file (SSRF). The method divides the process of selection into several stages and selects cooperative vehicles from the candidates; the decision sequence generated by SSRF determines the set of cooperative vehicles. Simulation and data analysis show that our method is effective in terms of delivered ratio and file delivered delay.
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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 | 0.001 |
| 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