Towards Network Lifetime Maximization: Sink Mobility Aware Multihop Scalable Hybrid Energy Efficient Protocols for Terrestrial WSNs
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Bibliographic record
Abstract
We propose two routing protocols for Terrestrial Wireless Sensor Networks (TWSNs): Hybrid Energy Efficient Reactive (HEER) and Multihop Hybrid Energy Efficient Reactive (MHEER) routing protocol. The main purpose of designing these protocols is to improve the network lifetime and particularly the stability period of the underlying network. In MHEER, the node with the maximum energy in a region becomes cluster head (CH) of that region for that particular round (or cycle) of time and the number of the CHs in each round remains the same. Our techniques outperform the well-known existing routing protocols: LEACH, TEEN, and DEEC in terms of stability period and network lifetime. We also calculate the confidence interval of all our results which helps us to visualize the possible deviation of our graphs from the mean value. We also implement sink mobility on HEER and MHEER. We refer to them as HEER-SM and MHEER-SM. Simulation results show that HEER-SM and MHEER-SM yield better network lifetime and stability region as compared to the counterpart techniques. We have also carried out simulations with 500 and 1000 nodes in the same field dimensions besides 100 nodes. Simulations prove that the proposed schemes show the same behavior with 500 and 1000 nodes; that is, HEER and MHEER are scalable as well.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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