EAM: Energy Aware Mobility over wireless sensor networks
Bibliographic record
Abstract
Mobility over wireless sensor networks (WSNs) has been largely studied, with many protocol enhancements investigated to support mobile nodes and dynamic topological changes in primarily static architectures. Many research efforts have also been devoted to optimize energy consumption in WSN by developing energy aware protocols and algorithms. On the other hand, there have been fewer studies devoted to managing mobility and energy consumption at the same time, with the aim to balance the node energy consumption for minimum disconnects and handoffs due to energy depletion problems. In this paper, we propose a mobility framework to do so, named Energy Aware Mobility (EAM) over WSN. It uses both the link strengths between a mobile node and potential static parent nodes, and the residual energy of the parent nodes to make handoff decisions, with the side benefit of balancing the node energy distribution across the WSN. We show through simulations the efficiency of the proposed framework in comparison with ignoring the node energy states or using a standard low power routing approach.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".