Energy Utilization-Aware Operation Control Algorithm in Energy Harvesting Base Stations
Bibliographic record
Abstract
Radio frequency (RF) energy transfer has received high attention as a promising technology for wireless sensor networks (WSNs) due to its flexibility of energy supply. However, unplanned RF energy transmissions may lead to increased energy consumption in the main grid. To address this problem, we first develop the energy queuing models for base station (BS) and sensor node (SN). Based on them, we propose an energy utilization-aware operation control algorithm (EU-OCA) to minimize the energy outage probabilities of SNs while maintaining the energy consumption of the main grid below a certain level. In EU-OCA, a controller determines jointly the active/sleep modes and the transmission powers of renewable energy-based BSs with the consideration of the statistical information on the energy arrival of BSs and the energy consumption of SNs. Evaluation results demonstrate that EU-OCA can achieve longer lifetime compared to other BS operation control algorithms while maintaining the energy consumption of the main grid below a target level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".