A secure and efficient RSU‐aided bundle forwarding protocol for vehicular delay tolerant networks
Bibliographic record
Abstract
Abstract Recently, vehicularad hocnetwork (VANET) has emerged as a promising approach for road safety and traffic efficiency improvement through a variety of vehicle applications enabled by communications between vehicles such as emergency braking warning, etc. However, due to its unique characteristics, such as intermittent connectivity due to high‐speed mobility of the network nodes (or vehicles), also known as vehicular delay tolerant network, it poses a major challenge to the realization of those applications. In this paper, we propose a new roadside unit (RSU) aided bundle forwarding protocol for vehicular delay tolerant networks. Furthermore, with the assistance from those RSUs deployed at some critical points on the road, for example, intersections, the proposed protocol can increase the network performance in terms of delivery ratio. At the same time, since vehicle‐to‐vehicle (V2V) and vehicle‐to‐RSU (V2R) privacy‐preserving authentications are guaranteed, the black (gray) hole attacks can be avoided. Extensive simulations demonstrate the effectiveness of the proposed protocol. Copyright © 2010 John Wiley & Sons, Ltd.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".