A Taxonomy and Survey of Microscopic Mobility Models from the Mobile Networking Domain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A mobility model is used to generate the trajectories of mobile nodes in simulations when developing new algorithms for mobile networks. A model must realistically reflect the scenario in which the technology will be used to reliably validate the algorithm. Considerable progress has been made toward realistic mobility models in the academic literature, and models have become quite complex. A consistent taxonomy has not yet been established for this field. A new multifaceted taxonomy is presented in this work that provides a framework for authors to clearly and consistently describe their models, making them easier to understand and reproduce. By surveying the application field of mobile communication networks, a common nomenclature and a high-level view of existing literature are provided, which are required to reduce duplication of effort and to enable a better sense of the way forward. A tactical scenario demonstrates the application of the taxonomy to model construction.
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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 | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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