Tuning guaranteed time slots of IEEE 802.15.4 for transformer health monitoring in the smart grid
Bibliographic record
Abstract
Wireless Sensor Networks (WSNs) are anticipated to become the preferred tools of choice for monitoring and controlling power utility assets in the smart grid due to their versatility. However, in some smart grid monitoring applications, data generation rates could fluctuate rapidly due to the sudden occurrence of critical faults or failures in the monitored equipment. As a consequence, critical data could experience excessive delays because of this increase in the packet arrival rates. In this paper, we present an Adaptive Guaranteed Time Slot (GTS) allocation scheme (AGTS) for IEEE 802.15.4-based WSNs used in high traffic intensity smart grid monitoring applications. AGTS scheme can adaptively reduce the end-to-end delay and flexibly tune the GTS to provide the required Quality of Service (QoS) differentiation to delay critical smart grid monitoring applications. The proposed scheme can adaptively allocate the needed GTS to nodes transmitting high priority traffic or draw back the unneeded GTS.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".