Energy-Efficient Secure NOMA-Enabled Mobile Edge Computing Networks
Why this work is in the frame
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Bibliographic record
Abstract
This paper considers a non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system in the presence of a malicious eavesdropper. We employ the partial offloading mode such that each user can divide the individual computation task into two parts for local executing and offloading, respectively. The secrecy outage probability is adopted to measure the secrecy performance of computation ofloading by considering the practically passive eavesdropping scenario. Under this setup, we investigate the problem of minimizing the weighted sum-energy consumption for all users, subject to the secrecy ofloading rates constraints, the computation latency constraints and the secrecy outage probability constraints, and then derive the semi-closed form solution for this problem. Numerical results are provided and demonstrate that the merits of our proposed design are better than those of the alternative benchmark schemes.
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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