Connectivity with Static Transmission Range in Vehicular Ad Hoc Networks
Bibliographic record
Abstract
Connectivity in mobile wireless ad-hoc networks is maintained by setting the transmission range so that a node can establish a link to any other node in the network either directly or over multiple hops. Many analytical and experimental studies have focused on determining the minimum transmission range (MTR) that provides connectivity while minimizing transceiver power for various levels of node densities. In this paper, we determine, using simulations, the MTR in vehicular ad hoc networks (VANET) of various road configurations. We show that in 1-lane, 2-lane, and 2-way roads, MTR values confirm the analytical relations developed in the literature for 1-dimensional networks until density increases beyond a critical vehicle density. Moreover, where traffic jams are forming at intersections, MTR values are not affected by the change in vehicle density. Therefore, a large static transmission range must be chosen in order to keep the network connected in all traffic scenarios.
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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".