Online UAV-Mounted Edge Server Dispatching for Mobile-to-Mobile Edge Computing
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
Mobile edge computing (MEC) has been considered as a promising technology to handle computation-intensive and delay-sensitive tasks in the Internet of Things (IoT) ecosystem, such as smart city and smart tourism. However, due to user mobility, edge servers with fixed deployment are not flexible enough to handle time-varying user tasks in hot-spot areas. In this article, a novel online unmanned aerial vehicle (UAV)-mounted edge server dispatching scheme is proposed to provide flexible mobile-to-MEC services. UAVs are dispatched to the appropriate hover locations by geographically merging tasks into several hot-spot areas. Theoretical analysis guarantees the worst case performance bound. Extensive evaluation driven by real-world mobile requests shows that while maintaining a good latency fairness, the mobile server dispatching scheme can serve more user equipments (UEs) as well as achieve a high resource utilization. Moreover, the hybrid scheme can satisfy even more user demands while dispatching fewer UAVs with a higher server utilization.
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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 | 0.000 |
| 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 it