Quadratic Estimation of Success Probability of Greedy Geographic Forwarding in Unmanned Aeronautical Ad-Hoc Networks
Bibliographic record
Abstract
Due to the availability of location information in unmanned aerial vehicles (UAVs), we propose to use geographic routing mechanisms as a core forwarding protocol in unmanned aeronautical ad-hoc networks (UAANETs) for the purpose of reducing routing overhead. As a result, this paper investigates the performance of the core forwarding mechanism i.e. the greedy geographic part. Since the forwarding mechanism for dynamic UAANETs with many statistical inter-dependencies is complex, a closed-form model does not exist. Therefore, a quadratic polynomial estimation is proposed for computing the success probability of greedy geographic forwarding based on the results of a set of realistic Monte Carlo simulations. This mathematical model can later be used to predict and evaluate the performance of other greedy-based geographic routing protocols for UAV applications.
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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".