Datasets:

ICOS-AI
/

scaphandre_cpu_usage

timestamp float64 1.75B 1.75B	cpu_usage float64 7.89 11.5
1,752,571,522.489	11.51
1,752,571,525.489	11.47
1,752,571,528.489	11.19
1,752,571,531.489	11.19
1,752,571,534.489	11.02
1,752,571,537.489	11.02
1,752,571,540.491	10.69
1,752,571,543.489	10.64
1,752,571,546.489	10.64
1,752,571,549.489	10.75
1,752,571,552.489	10.75
1,752,571,555.489	10.85
1,752,571,558.489	10.46
1,752,571,561.491	10.46
1,752,571,564.489	10.42
1,752,571,567.489	10.42
1,752,571,570.491	10.47
1,752,571,573.489	10.51
1,752,571,576.489	10.51
1,752,571,579.489	10.15
1,752,571,582.489	10.15
1,752,571,585.489	10.14
1,752,571,588.489	10.05
1,752,571,591.489	10.05
1,752,571,594.489	10.12
1,752,571,597.489	10.12
1,752,571,600.492	10.11
1,752,571,603.489	10.18
1,752,571,606.489	10.18
1,752,571,609.489	10.01
1,752,571,612.489	10.01
1,752,571,615.489	10.09
1,752,571,618.489	10
1,752,571,621.491	10
1,752,571,624.489	10
1,752,571,627.489	10
1,752,571,630.489	9.92
1,752,571,633.489	10.01
1,752,571,636.489	10.01
1,752,571,639.489	10.01
1,752,571,642.489	10.01
1,752,571,645.489	10.09
1,752,571,648.489	9.84
1,752,571,651.491	9.84
1,752,571,654.489	9.77
1,752,571,657.489	9.77
1,752,571,660.491	9.71
1,752,571,663.489	9.89
1,752,571,666.489	9.89
1,752,571,669.489	9.82
1,752,571,672.489	9.82
1,752,571,675.489	9.92
1,752,571,678.489	9.76
1,752,571,681.489	9.76
1,752,571,684.489	9.94
1,752,571,687.489	9.94
1,752,571,690.489	9.87
1,752,571,693.489	9.96
1,752,571,696.489	9.96
1,752,571,699.489	9.88
1,752,571,702.489	9.88
1,752,571,705.489	9.97
1,752,571,708.489	9.65
1,752,571,711.492	9.65
1,752,571,714.489	9.6
1,752,571,717.489	9.6
1,752,571,720.491	9.47
1,752,571,723.489	9.43
1,752,571,726.489	9.43
1,752,571,729.489	9.16
1,752,571,732.489	9.16
1,752,571,735.489	9.23
1,752,571,738.489	9.37
1,752,571,741.491	9.37
1,752,571,744.489	9.58
1,752,571,747.489	9.58
1,752,571,750.491	9.61
1,752,571,753.489	9.8
1,752,571,756.489	9.8
1,752,571,759.489	9.74
1,752,571,762.489	9.74
1,752,571,765.489	9.68
1,752,571,768.489	9.39
1,752,571,771.491	9.39
1,752,571,774.489	9.43
1,752,571,777.489	9.43
1,752,571,780.489	9.48
1,752,571,783.489	9.6
1,752,571,786.489	9.6
1,752,571,789.489	9.55
1,752,571,792.489	9.55
1,752,571,795.489	9.75
1,752,571,798.489	9.93
1,752,571,801.492	9.93
1,752,571,804.489	9.86
1,752,571,807.489	9.86
1,752,571,810.492	9.55
1,752,571,813.489	9.5
1,752,571,816.489	9.5
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)

Downloads last month: 15

Size of downloaded dataset files:

7.2 kB

Size of the auto-converted Parquet files:

4.3 kB

Number of rows:

300