Reliable Energy Aware Routing In Wireless Sensor Networks
Why this work is in the frame
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Bibliographic record
Abstract
The main purpose of a sensor network is information gathering and delivery. Therefore, the quantity and quality of the data delivered to the end-user is very important. The immense potential of wireless sensor networks (WSNs) has created a growing awareness of the need for reliability in such networks. A major concern in the design of WSN protocols, including those concerned with reliability, is energy efficiency. In this paper, we present a novel approach to reliability in WSNs. We introduce REAR (reliable energy aware routing), which is a distributed, on-demand, reactive routing protocol that is intended to provide a reliable transmission environment for data packet delivery. REAR introduces local node selection, path reservation and path request broadcasting delay to provide a reliable transmission environment to reduce retransmissions caused by unstable paths. The scheme efficiently utilizes the limited energy and available memory resources of sensor nodes. REAR attempts to take precaution against errors, instead of finding a solution after encountering the errors. Simulation experiments show that, by deploying an energy reservation scheme, REAR outperforms traditional schemes by establishing an energy-sufficient path from the sink to the source with special path request flooding, and also by distributing the traffic load more evenly in the network
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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