Federated Network Utility Maximization

We consider a large-scale optimization problem with private utilities over a network where servers are connected through a graph and each server has their own edge devices connected to it. This setup finds applications in many network architectures from wireless communications to power networks and to supply chain management. Over this architecture, we provide a decentralized federated optimization algorithm that uses decomposition methods along with a single round of consensus exchange on the global dual variables. The convergence performance of the method is illustrated with numerical examples.