Energy Efficient Packet Transmission Strategies for Wireless Body Area Networks with Rechargeable Sensors
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Bibliographic record
Abstract
In this paper, we investigate energy efficient packet transmission strategies for wireless body area networks (WBANs) with rechargeable sensors. For practical implementations, we propose a multi-threshold based transmission strategy by taking into account the channel state, battery state and number of buffered packets in the system. A discrete Markov arrival process (DMAP) is introduced to jointly model channel correlations and energy allocations. After that, with given thresholds and corresponding energy allocations, a level dependent Quasi-Birth- and-Death Markov chain is constructed to evaluate the system performance. According to the derived performance metrics, we formulate an optimization problem to find optimal thresholds for energy efficiency maximization with reasonable performance provisioning. Extensive simulations are conducted to verify our proposed queueing analytical model and demonstrate perfor- mance gains of our proposed strategy.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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