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float64 1.75B
1.75B
| ram_usage
float64 14.9k
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1,752,571,570.491
| 19,746.445313
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1,752,571,573.489
| 18,952.699219
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1,752,571,576.489
| 19,728.773438
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1,752,571,579.489
| 18,139.105469
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1,752,571,582.489
| 16,712.9375
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1,752,571,585.489
| 18,470.90625
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1,752,571,588.489
| 20,013.796875
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1,752,571,591.489
| 15,876.023438
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1,752,571,594.489
| 17,726.316406
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1,752,571,597.489
| 19,204.488281
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1,752,571,600.492
| 18,643.386719
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1,752,571,603.489
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1,752,571,606.489
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1,752,571,609.489
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1,752,571,612.489
| 16,462.3125
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1,752,571,615.489
| 18,217.15625
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1,752,571,618.489
| 19,768.605469
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1,752,571,621.491
| 17,163.523438
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1,752,571,624.489
| 18,740.703125
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1,752,571,627.489
| 19,925.195313
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1,752,571,630.489
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1,752,571,633.489
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1,752,571,636.489
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1,752,571,639.489
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1,752,571,642.489
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1,752,571,645.489
| 19,067.464844
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1,752,571,648.489
| 20,284.015625
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1,752,571,651.491
| 16,832.320313
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1,752,571,654.489
| 18,462.917969
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1,752,571,657.489
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1,752,571,660.491
| 18,272.261719
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1,752,571,663.489
| 17,494.214844
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1,752,571,666.489
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1,752,571,669.489
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1,752,571,672.489
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1,752,571,675.489
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1,752,571,678.489
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1,752,571,681.489
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1,752,571,684.489
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1,752,571,687.489
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1,752,571,690.489
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1,752,571,699.489
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1,752,571,702.489
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1,752,571,705.489
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1,752,571,708.489
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1,752,571,711.492
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1,752,571,714.489
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1,752,571,717.489
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1,752,571,720.491
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1,752,571,726.489
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1,752,571,729.489
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1,752,571,732.489
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1,752,571,735.489
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1,752,571,741.491
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1,752,571,744.489
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1,752,571,747.489
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1,752,571,750.491
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1,752,571,753.489
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1,752,571,756.489
| 19,106.945313
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1,752,571,759.489
| 19,789.109375
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1,752,571,762.489
| 18,311.367188
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1,752,571,765.489
| 19,507.175781
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1,752,571,768.489
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1,752,571,771.491
| 15,528.242188
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1,752,571,774.489
| 17,441.105469
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1,752,571,777.489
| 19,083.207031
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1,752,571,780.489
| 18,575.394531
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1,752,571,783.489
| 17,817.324219
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1,752,571,786.489
| 18,869.847656
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1,752,571,789.489
| 20,436.03125
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1,752,571,792.489
| 16,399.535156
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1,752,571,795.489
| 18,152.308594
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1,752,571,798.489
| 19,704.320313
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1,752,571,801.492
| 17,787.796875
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1,752,571,804.489
| 19,182.515625
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1,752,571,807.489
| 20,213.46875
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1,752,571,810.492
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1,752,571,813.489
| 18,097.210938
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1,752,571,816.489
| 19,131.90625
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1,752,571,819.489
| 18,028.347656
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1,752,571,822.489
| 16,641.789063
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1,752,571,825.489
| 18,305.242188
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1,752,571,828.489
| 19,861.015625
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1,752,571,831.489
| 15,718.25
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1,752,571,834.489
| 17,609.914063
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1,752,571,837.489
| 19,098.542969
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1,752,571,840.491
| 19,901.378906
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1,752,571,843.489
| 18,854.984375
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1,752,571,846.489
| 19,635.5625
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1,752,571,849.489
| 16,969.753906
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1,752,571,852.489
| 15,522.34375
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1,752,571,855.489
| 17,564.246094
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1,752,571,858.489
| 19,370.714844
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1,752,571,861.491
| 16,308.800781
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1,752,571,864.489
| 18,104.71875
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1,752,571,867.489
| 19,423.050781
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in Data Studio
Scaphandre RAM Usage Dataset
Dataset Description
This dataset contains RAM usage monitoring data collected using Scaphandre for the ICOS Federated Learning infrastructure.
Overview
- Source: Scaphandre energy monitoring tool
- Collection Method: Live system monitoring (continuous fetching)
- Purpose: Training data for ICOS FL
- Update Frequency: Real-time collection with 3s intervals
Data Schema
| Column | Type | Description |
|---|---|---|
| timestamp | float | Unix timestamp of measurement |
| ram_usage | float | Memory usage in MB or percentage |
Usage in ICOS FL
This dataset is used during the ICOS Federated Learning training process. Note that actual training uses live-fetched data, so values change continuously.
ICOS Project Context
Part of the ICOS meta-operating system for the edge-cloud continuum, focusing on:
- Service performance optimization
- Resource consumption monitoring
- Memory efficiency in edge deployments
Funded by the European Union's Horizon programme (Grant No 101070177)
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