3 papers
cs.NI2026
HybridFLow: SDN-Orchestrated Client Partitioning for Hybrid Federated Learning
Osama Abu Hamdan, Rabin Pandey, Hao Che +2
Cross-silo Federated Learning (FL) enables geographically distributed institutions to collaboratively train machine learning models without sharing raw data. In wide-area deploymen…
cs.NI2025
FLEET: A Federated Learning Emulation and Evaluation Testbed for Holistic Research
Osama Abu Hamdan, Hao Che, Engin Arslan +1
Federated Learning (FL) presents a robust paradigm for privacy-preserving, decentralized machine learning. However, a significant gap persists between the theoretical design of FL…
cs.NI2025
SmartFLow: A Communication-Efficient SDN Framework for Cross-Silo Federated Learning
Osama Abu Hamdan, Hao Che, Engin Arslan +1
Cross-silo Federated Learning (FL) enables multiple institutions to collaboratively train machine learning models while preserving data privacy. In such settings, clients repeatedl…