RE-ATTEMPT: A New Energy-Efficient Routing Protocol for Wireless Body Area Sensor Networks
Bibliographic record
Abstract
Modern health care system is one of the most popular Wireless Body Area Sensor Network (WBASN) applications and a hot area of research subject to present work. In this paper, we present Reliability Enhanced-Adaptive Threshold based Thermal-unaware Energy-efficient Multi-hop ProTocol (RE-ATTEMPT) for WBASNs. The proposed routing protocol uses fixed deployment of wireless sensors (nodes) such that these are placed according to energy levels. Moreover, we use direct communication for the delivery of emergency data and multihop communication for the delivery of normal data. RE-ATTEMPT selects route with minimum hop count to deliver data which downplays the delay factor. Furthermore, we conduct a comprehensive analysis supported by MATLAB simulations to provide an estimation of path loss, and problem formulation with its solution via linear programming model for network lifetime maximization is also provided. In simulations, we analyze our protocol in terms of network lifetime, packet drops, and throughput. Results show better performance for the proposed protocol as compared to the existing one.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".