Cross-Layer Design for Energy Conservation in Wireless Sensor Networks
Why this work is in the frame
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Bibliographic record
Abstract
Wireless sensor networks (WSNs) require energy- efficient protocols to improve the network lifetime. In this work, we adopt a cross-layer strategy that considers routing and MAC layers jointly. At the routing layer, we propose balancing the traffic through the WSN. We show that sending the traffic generated by each sensor node through multiple paths instead of using a single path allows significant energy conservation. On the other hand, at the MAC layer, we propose to control the retry limit of retransmissions over each wireless link. We show that by efficiently adjusting the retry limit for each link, further energy conservation can be achieved, improving thus the network lifetime. A new analytical model for the joint optimization system is complemented by simulations in order to quantitatively evaluate the benefits of our proposal.
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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 | 0.001 |
| 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