Behavior of clock-sampling mutual network synchronization in wireless sensor networks
Why this work is in the frame
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Bibliographic record
Abstract
Clock synchronization is an important component of wireless sensor networks both for co-ordination of node communications and for time stamping sensor data. The properties of the previously presented clock sampling mutual network synchronization algorithm (CS-MNS) are explored. The desirable properties of this algorithm include simplicity, low communication and processing overhead, and fully decentralized operation. Past simulation and analysis has shown clock convergence under specific conditions in single hop networks. We show that in the absence of offset errors the network clocks converge. In the presence of offset error we present conditions on the degree on clock asynchrony under which the network clock rates show convergent behavior. The analysis is applicable as long as the network topology is connected and thus is of interest in both single-hop and multi-hop environments. We show how the network designer can use these conditions to add a bias term to the CS-MNS algorithm and thus improve the start-up dynamics of the algorithm. Additionally, we discuss the algorithm from a security standpoint. Finally, we propose a method for adding external reference synchronization that is compatible with our security discussion.
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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 | 0.002 |
| 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