An enhanced Gauss-Markov mobility model for simulations of unmanned aerial ad hoc networks
Why this work is in the frame
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Bibliographic record
Abstract
Routing protocols are designed assuming certain application-specific network characteristics. In order for a routing protocol to be effective and reliable it needs to be evaluated with a realistic mobility model. The Random Waypoint mobility model, widely used, allows node to stop suddenly and turn sharply, and therefore fails to capture the movement pattern of actual airborne vehicles. In this paper we propose the Enhanced Gauss-Markov (EGM) mobility model, a realistic model for networks of UAVs (UAANETs) based on the Gauss-Markov (GM) mobility model. EGM features mechanisms to eliminate/limit sudden stops and sharp turns within the simulation region. The model, unlike others, also deals explicitly with ensuring smooth trajectories at the boundaries. Simulations in OPNET show that EGM, compared to RWP, results in many more network partitions. This then suggests that network partitioning is a significant issue that ought to be dealt with in the protocol design for UAANETs.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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 it