ICOS-FL Documentation¶
ICOS-FL is a federated learning framework for real-time resource monitoring built on Flower. It enables distributed training of LSTM models for predicting system metrics like CPU usage, memory consumption, and power usage across ICOS nodes.
Project Links
Features¶
Federated Learning: Train models across distributed nodes while keeping data local
Real-time Monitoring: Track CPU, memory, and power consumption metrics
LSTM Prediction: Forecast resource usage with configurable time windows
DataClay Integration: Efficient storage and retrieval of time series data
Docker Deployment: Easy setup with containerized components