Semantic and self-decision geocast protocol for data dissemination over VANET (SAS-GP)
Bibliographic record
Abstract
In this paper, a semantic and self-decision geocast routing protocol for disseminating safety and non-safety information over VANET (SAS-GP) is presented. SAS-GP initially executes an algorithm for locally determining the semantic geocast area. Then, the protocol disseminates the information in three phases: Spread, Preserve, and Assurance, which utilize the traffic information system and the digital map. SAS-GP principally employs timer-based techniques in order to avoid overhead; nonetheless, novel factors are enhanced to calculate the values of each timer in the three phases. Simulation results demonstrate effective and reliable dissemination in terms of delivery ratio and number of false warning compared to existing protocols when evaluated in high scale and realistic scenarios. Also, SAS-GP performs faster in notifying vehicles resulting a higher geocast distance before approaching the location of the event.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".