Ad-ATMA: An Efficient MAC protocol for Wireless Sensor and Ad Hoc Networks
Why this work is in the frame
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Bibliographic record
Abstract
Efficient medium access control (MAC) algorithms are needed for nodes to share a transmission medium and achieve a high throughput. A MAC algorithm schedules packet transmissions so as to that minimize the time taken to send the packets without collisions. In wireless ad hoc and sensor networks, a MAC algorithm must conserve energy as well as provide good throughput. Most existing MAC algorithms for wireless networks are designed to work well under low traffic rates. In this paper we propose a new distributed algorithm Ad-ATMA for wireless ad hoc and sensor networks under relatively high traffic rates. We demonstrate using simulations that Ad-ATMA outperforms the best existing algorithms designed for higher traffic rates in terms of packet delivery ratio and latency while consuming almost identical energy as them.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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