This work integrates peer-to-peer federated learning tools with NS3, a widely used network simulator, to create a novel simulator designed to allow heterogeneous device experiments in federated learning. This cross-platform adaptability addresses a critical gap in existing simulation tools, enhancing the overall utility and user experience. NS3 is leveraged to simulate WiFi dynamics to facilitate federated learning experiments with participants that move around physically during training, leading to dynamic network characteristics. Our experiments showcase the simulator's efficiency in computational resource utilization at scale, with a maximum of 450 heterogeneous devices modelled as participants in federated learning. This positions it as a valuable tool for simulation-based investigations in peer-to-peer federated learning. The framework is open source and available for use and extension to the community.

翻译：本研究将对等联邦学习工具与广泛使用的网络模拟器NS3相结合，创建了一种新型模拟器，旨在支持联邦学习中异构设备的实验。这种跨平台适应性解决了现有模拟工具的关键空白，提升了整体实用性和用户体验。通过利用NS3模拟WiFi动态特性，该模拟器能够支持参与者在训练期间物理移动的联邦学习实验，从而产生动态网络特征。实验证明该模拟器在大规模计算资源利用方面具有高效性，最多可模拟450个异构设备作为联邦学习参与者。这使其成为对等联邦学习领域基于模拟研究的重要工具。该框架已开源，可供社区使用和扩展。