Federated Networks

Federated Networks are a decentralized network architecture where multiple independent networks or systems interconnect and share resources while maintaining autonomy. This approach enables interoperability, data exchange, and collaboration across disparate domains without requiring a central authority. It is commonly used in contexts like federated identity management, federated learning, and federated databases to enhance scalability and privacy.

Also known as: Federated Systems, Federation Networks, FedNets, Federated Architecture, Network Federation

Why learn Federated Networks?

Developers should learn about Federated Networks when building systems that need to operate across organizational boundaries, such as in healthcare, finance, or IoT applications, where data sovereignty and privacy are critical. It is essential for implementing federated identity systems like OAuth or SAML, federated learning in AI to train models on distributed data without centralizing it, and federated databases for querying across multiple sources while preserving local control.

Learning Resources

• docs: Federated Networks: Concepts and Applications
• course: Introduction to Federated Learning and Networks
• tutorial: Federated Identity Management with OAuth and SAML
• tutorial: Federated Networks in IoT: A Tutorial
• book: Building Federated Systems - Book