Exploiting External Interference for Clock Synchronization
Bibliographic record
Abstract
Many wireless sensor network (WSN) applications require the synchronization of the network's independent node clocks. That synchronization is a challenging problem that often requires energy-constrained devices to exchange many messages.This paper introduces the Interference-based Clock Synchronization (ICS) protocol, an approach suitable for dense WSNs located in urban environments. ICS uses external interference to synchronize the network's nodes to either a network-local internal or global (e.g., UTC) external time. All of the network's nodes observe interference at roughly the same time, and the node possessing the common time transmits its observed pattern to the network. The network nodes then compare and align the received and locally-observed patterns, and subsequently, they update their clocks to the common time.The protocol is evaluated using both a simulator and hardware. Using this approach, the number of transmitted messages scales linearly with the network size. In the simulator, ICS-synchronized clocks had a mean time difference of 0.3635 ms when compared with the common time. Using hardware, the difference was larger at 4.9388 ms, but much of that difference can likely be attributed to the experimental setup.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".