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float64 1.75B
1.75B
| cpu_usage
float64 7.89
11.5
|
|---|---|
1,752,571,522.489
| 11.51
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1,752,571,525.489
| 11.47
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1,752,571,528.489
| 11.19
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1,752,571,531.489
| 11.19
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1,752,571,534.489
| 11.02
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1,752,571,537.489
| 11.02
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1,752,571,540.491
| 10.69
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1,752,571,543.489
| 10.64
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1,752,571,546.489
| 10.64
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1,752,571,549.489
| 10.75
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1,752,571,552.489
| 10.75
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1,752,571,555.489
| 10.85
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1,752,571,558.489
| 10.46
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1,752,571,561.491
| 10.46
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1,752,571,564.489
| 10.42
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1,752,571,567.489
| 10.42
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1,752,571,570.491
| 10.47
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1,752,571,573.489
| 10.51
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1,752,571,576.489
| 10.51
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1,752,571,579.489
| 10.15
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1,752,571,582.489
| 10.15
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1,752,571,585.489
| 10.14
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1,752,571,588.489
| 10.05
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1,752,571,591.489
| 10.05
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1,752,571,594.489
| 10.12
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1,752,571,597.489
| 10.12
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1,752,571,600.492
| 10.11
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1,752,571,603.489
| 10.18
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1,752,571,606.489
| 10.18
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1,752,571,609.489
| 10.01
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1,752,571,612.489
| 10.01
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1,752,571,615.489
| 10.09
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1,752,571,618.489
| 10
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1,752,571,621.491
| 10
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1,752,571,624.489
| 10
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1,752,571,627.489
| 10
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1,752,571,630.489
| 9.92
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1,752,571,633.489
| 10.01
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1,752,571,636.489
| 10.01
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1,752,571,639.489
| 10.01
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1,752,571,642.489
| 10.01
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1,752,571,645.489
| 10.09
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1,752,571,648.489
| 9.84
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1,752,571,651.491
| 9.84
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1,752,571,654.489
| 9.77
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1,752,571,657.489
| 9.77
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1,752,571,660.491
| 9.71
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1,752,571,663.489
| 9.89
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1,752,571,666.489
| 9.89
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1,752,571,669.489
| 9.82
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1,752,571,672.489
| 9.82
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1,752,571,675.489
| 9.92
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1,752,571,678.489
| 9.76
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1,752,571,681.489
| 9.76
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1,752,571,684.489
| 9.94
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1,752,571,687.489
| 9.94
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1,752,571,690.489
| 9.87
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1,752,571,693.489
| 9.96
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1,752,571,696.489
| 9.96
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1,752,571,699.489
| 9.88
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1,752,571,702.489
| 9.88
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1,752,571,705.489
| 9.97
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1,752,571,708.489
| 9.65
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1,752,571,711.492
| 9.65
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1,752,571,714.489
| 9.6
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1,752,571,717.489
| 9.6
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1,752,571,720.491
| 9.47
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1,752,571,723.489
| 9.43
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1,752,571,726.489
| 9.43
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1,752,571,729.489
| 9.16
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1,752,571,732.489
| 9.16
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1,752,571,735.489
| 9.23
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1,752,571,738.489
| 9.37
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1,752,571,741.491
| 9.37
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1,752,571,744.489
| 9.58
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1,752,571,747.489
| 9.58
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1,752,571,750.491
| 9.61
|
1,752,571,753.489
| 9.8
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1,752,571,756.489
| 9.8
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1,752,571,759.489
| 9.74
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1,752,571,762.489
| 9.74
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1,752,571,765.489
| 9.68
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1,752,571,768.489
| 9.39
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1,752,571,771.491
| 9.39
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1,752,571,774.489
| 9.43
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1,752,571,777.489
| 9.43
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1,752,571,780.489
| 9.48
|
1,752,571,783.489
| 9.6
|
1,752,571,786.489
| 9.6
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1,752,571,789.489
| 9.55
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1,752,571,792.489
| 9.55
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1,752,571,795.489
| 9.75
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1,752,571,798.489
| 9.93
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1,752,571,801.492
| 9.93
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1,752,571,804.489
| 9.86
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1,752,571,807.489
| 9.86
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1,752,571,810.492
| 9.55
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1,752,571,813.489
| 9.5
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1,752,571,816.489
| 9.5
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1,752,571,819.489
| 9.38
|
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Scaphandre CPU Usage Dataset
Dataset Description
This dataset contains CPU 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 |
| cpu_usage | float | CPU utilization percentage (0-100) |
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
- Power efficiency in edge deployments
Funded by the European Union's Horizon programme (Grant No 101070177)
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