WSN10-6: An Energy Consumption Study of Wireless Sensor Networks with Delay-Constrained Traffic
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Bibliographic record
Abstract
Many mission-critical applications of wireless sensor networks generate traffic that have a stringent delay requirement. In this paper, we study the effects of relaying delay- constrained traffic in a wireless sensor network according to two different strategies. The first strategy allows traffic splitting, in which data flow can be split and sent on multiple paths from the source to the destination. The second strategy disallows traffic splitting, in which data flow cannot be split and must be sent on a single path from the source to the destination. We present a model based on linear and integer linear programming for finding an optimal allocation of splittable and unsplittable traffic in a wireless sensor network, in which traffic is subject to soft delay constraints. The objective is to minimize the total energy consumption spent on communication and the penalty incurred from the violation of delay constraints. Based on this model, we perform an empirical analysis to quantify the performance gains and losses of a splittable and unsplittable traffic allocation strategy for wireless sensor networks with delay-constrained traffic. The experiment results show that splitting traffic does not provide a significant advantage in energy consumption, but can afford strategies for relaying data with a lower delay penalty.
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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