DEAC: Depth and Energy Aware Cooperative Routing Protocol for Underwater Wireless Sensor Networks
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Bibliographic record
Abstract
In Underwater Wireless Sensor Networks (UWSNs), reliability is one of the major concerns for large number of applications. The underwater environment is very harsh and noisy. Fading is common and unavoidable, therefore achieving reliable data transfer requires innovative routing solutions. This paper presents a energy efficient cooperative routing with varying Depth threshold (Dth) called Depth and Energy Aware Cooperative Routing Protocol for UWSNs (DEAC). DEAC utilizes the broadcast nature of sensor nodes by performing cooperative routing. Optimised value of Dth is selected for a source node and varied according to the number of alive neighbors of that source node. Potential destination node is selected from outside of Dth and a potential relay node is selected from inside. Destination and relay are selected on the basis of depth, residual energy and link quality between sensor nodes. Source node forwards a data packet to destination node from two ways, directly from source node to destination node and via relay to destination node. At destination, two data packets received from source node and relay node are combined using Maximum Ratio Combining Technique (MRC). Simulation results show that DEAC achieves better performance over some existing depth based routing protocols in terms of throughput, packet Acceptance ratio, packet drop and energy consumption.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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