Summary
As digital infrastructure grows increasingly dependent on real-time data from distributed sensors and devices, the need to monitor network traffic locally and reliably becomes crucial. This project addresses a critical challenge in edge computing, i.e., how to provide accurate and up-to-date data to Edge AI applications while preserving user privacy and minimizing communication overhead. Traditional methods struggle with outdated data, privacy limitations, and limited processing power at the edge. This research seeks to develop a novel data synthesis framework that enables edge devices to gene
