Reliable Emergency Message Dissemination Scheme for Urban Vehicular Networks
Bibliographic record
Abstract
Vehicular safety applications based on DSRC/802.11p have strict reliability requirement (greater than 0.99). However, it is difficult to achieve high reliability in wireless medium as the transmission is vulnerable to various wave propagation issues. To the best of our knowledge, none of the existing emergency message dissemination schemes in the literature, achieves a predefined reliability in lossy channel. In this paper, we propose a novel scheme, called reliable emergency message dissemination scheme (REMD), which achieves a predefined reliability for message dissemination while satisfying delay requirements, for various channel conditions. We aim to guarantee very high reliability (e.g., 99%) in each hop, with low control overhead while keeping low end-to-end latency for time-critical applications. We employ zero-correlated unipolar orthogonal codes to combat hidden terminal problem. We exploit periodic beacons, to accurately estimate reception quality of 802.11p wireless link in each cell; then, we use this information to determine the optimal number of broadcast repetitions in each hop. In addition, to ensure reliability in multi-hop, we utilize cooperative communication. The simulation results show that REMD outperforms the existing well-known schemes in the literature. Furthermore, REMD satisfies latency requirements for time-critical vehicular applications and has less network overhead than the existing schemes.
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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".