Evaluating Softwarization Gains in Drone Networks
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
Unmanned Aerial Systems (UASs) or drones are becoming increasingly dependable tools for many civil and industrial applications. Due to the increasing usage and capabilities of drones coupled with advances in innovative technologies and algorithms for managing and conducting tasks, drones are expected to crowd low-altitude airspace in urban areas. This brings many opportunities for service providers to provide drone-related services. Hence, efficient use of drones is required. In this paper, we investigate the benefits of reconfigurable softwarized drones operated by an entity or a service provider to perform tasks for its operations or for interested customers. We model a system of reconfigurable drones that can conduct multiple tasks per flight using Virtual Network Functions (VNFs) running on on-board capable computing systems. We compare our proposed model with alternatives with limited and no softwarization capabilities. Our evaluation demonstrates the performance gains due to reconfigurability in softwarized drone networks. Results show that softwarization allows drones to perform a variety of tasks using a limited number of reconfigurable drones and in a shorter time.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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