Evaluating the effectiveness of Situational Awareness dissemination in tactical mobile ad hoc networks
Why this work is in the frame
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Bibliographic record
Abstract
Situational Awareness (SA) dissemination in tactical mobile ad hoc networks (MANETs) plays an essential role in command and control systems for military operations. This task is particularly difficult in highly dynamic and complex environments with strict resource constraints on mobile units. In this work we present a design of SA dissemination schemes based on the multipoint relay (MPR) technique. We implement the schemes on a simulation platform and investigate their effectiveness in a real-time manner using novel metrics focusing on the completeness and freshness of SA, as well as the network traffic overhead and local processing cost. Two mobile scenarios, including one that is based on the Reference Point Group Mobility model, are set up to simulate the real-world behavior of tactical MANETs. The MPR-based methods are compared against an alternative scheme, Opportunistic Situational Awareness Passing, where the simulations highlight tradeoffs and provide insight into selection of design parameters.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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