  This paper introduces a Modified User Datagram Protocol (UDP) for Federated
Learning to ensure efficiency and reliability in the model parameter transport
process, maximizing the potential of the Global model in each Federated
Learning round. In developing and testing this protocol, the NS3 simulator is
utilized to simulate the packet transport over the network and Google
TensorFlow is used to create a custom Federated learning environment. In this
preliminary implementation, the simulation contains three nodes where two nodes
are client nodes, and one is a server node. The results obtained in this paper
provide confidence in the capabilities of the protocol in the future of
Federated Learning therefore, in future the Modified UDP will be tested on a
larger Federated learning system with a TensorFlow model containing more
parameters and a comparison between the traditional UDP protocol and the
Modified UDP protocol will be simulated. Optimization of the Modified UDP will
also be explored to improve efficiency while ensuring reliability.
