LEMoNet; Low Energy Wireless Sensor Network Design for Data Center Monitoring
Bibliographic record
Abstract
Today's data centers (DCs) consume up to 3% of the energy produced worldwide, much of which is wasted due to over-cooling and under utilization of IT equipment. This wastage in part stems from the lack of real-time visibility of fine-grained thermal distribution in DCs. Wireless sensing is an ideal candidate for DC monitoring as it is cost-effective, facility-friendly, and can be easily re-purposed. In this paper, we develop LEMoNet, a novel low-energy battery operated wireless sensor network design for monitoring DCs. It employs a two-tier network architecture and a multi-mode data exchange protocol to balance the trade-offs between low power consumption and high data reliability. We have evaluated the performance of LEMoNet by deploying custom-designed sensor and gateway nodes in a production DC as well as through extensive simulation studies in networks of various sizes. We show experimentally that LEMoNet achieves an average data yield over 98 % in the production DC. It scales well in large and dense networks in large-scale simulations. Under normal operations with one temperature and one humidity reading every thirty seconds, the battery lifetime of LEMoN et sensor nodes is projected to be 14.9 years on a single lithium coin battery.
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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 | 0.001 | 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 | 0.001 |
| 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".