论文标题
用于联合学习数据包传输的修改后的UDP
A Modified UDP for Federated Learning Packet Transmissions
论文作者
论文摘要
本文介绍了一个修改后的用户数据报协议（UDP），用于联合学习，以确保模型参数传输过程中的效率和可靠性，从而在每个联合学习回合中最大程度地发挥全局模型的潜力。在开发和测试此协议时，使用NS3模拟器通过网络模拟数据包传输，而Google TensorFlow用于创建自定义的联合学习环境。在此初步实现中，模拟包含三个节点，其中两个节点是客户端节点，一个是服务器节点。本文获得的结果对未来联合学习的协议能力提供了信心，因此，将来将在较大的联合学习系统上测试修改后的UDP，其张曲流模型包含更多参数，并在传统的UDP协议和修改后的UDP协议之间进行比较。还将探索修改后的UDP的优化，以提高效率，同时确保可靠性。
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.
