Minimizing AoI under Covertness Constraints in Internet of Things 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
Covertly collecting the latest status information is great crucial for the controller to make decision in Internet of Things (IoT) networks. In this paper, age of information (AoI) is leveraged to evaluate the information freshness. To improve the information freshness, packet re-transmission is exploited at the transmitter, while the re-transmission increases the probability that the transmission behavior is being detected by the adversaries. Hence, we propose a time constrained re-transmission strategy to make a trade-off between the AoI and transmission covertness. Specifically, the maximum allowable re-transmission times have different effects on the AoI and transmission covertness. We formulate an optimization problem to minimize AoI under the constraint of system covertness. The closed-form expression of the average AoI and the expected probability of error detection are derived. Then, the number of maximum re-transmission time slots is optimized to minimize the average AoI. Finally, numerical results demonstrate that the optimal choice of the re-transmission times is the upper bound value of the consecutive transmission time slots that satisfies the covertness constraint. Proposed retransmission strategy can guarantee the information freshness under a given covertness constraint.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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