Urgency-Based MAC Protocol for Wireless Sensor Body Area Networks
Bibliographic record
Abstract
In this paper, an Urgency-based MAC (U-MAC) protocol, in which sensor nodes reporting urgent health information are given higher priority by cutting-off the number of packet retransmission of sensor nodes with non urgent health information, is proposed. The main consideration of this work is providing Quality of Service (QoS) support in medical wireless sensor networks through differentiating nodal access to the medium. The proposed MAC protocol is mathematically analyzed considering a beacon-enabled star network configuration of the IEEE 802.15.4a standard at 2.4 GHz. The used wireless body area network (WBAN) consists of N sensor nodes controlled by a single network coordinator. The obtained performance results show the capability of the proposed UMAC protocol in providing service differentiation in medical WBAN. Also, the results show that the number of critical nodes that can be supported by WBAN and their packet arrival rates decrease as the number of packet retransmission of such nodes is increased.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".