论文标题
D2D无线联合学习的基于环拓扑的沟通效率方案
A Ring Topology-based Communication-Efficient Scheme for D2D Wireless Federated Learning
论文作者
论文摘要
联合学习(FL)是一种旨在提高分布式网络中通信效率的新兴技术,许多客户经常要求同时将其计算出的参数传输到FL服务器。但是,在无线网络中,由于不可靠的无线传输和有限的带宽,上述机制可能会导致长时间的传输时间。本文提出了一种通信方案,以最大程度地减少无线网络中FL的上行链路传输时间。提出的方法由两个主要要素组成,即修改的环(MRAR)架构,该构建结构集成了D2D无线通信以促进FL中的通信过程,以及一种修改的蚂蚁菌落优化算法,以识别MRAR体系结构的最佳组成。数值结果表明,与常规恒星拓扑相比,我们所提出的方法很健壮,可以显着减少传输时间。值得注意的是,与基线策略相比,上行链路传输时间的减少在适用于大规模FL的情况下可能是很大的,在该场景中,客户设备分布密度分布。
Federated learning (FL) is an emerging technique aiming at improving communication efficiency in distributed networks, where many clients often request to transmit their calculated parameters to an FL server simultaneously. However, in wireless networks, the above mechanism may lead to prolonged transmission time due to unreliable wireless transmission and limited bandwidth. This paper proposes a communication scheme to minimize the uplink transmission time for FL in wireless networks. The proposed approach consists of two major elements, namely a modified Ring All-reduce (MRAR) architecture that integrates D2D wireless communications to facilitate the communication process in FL, and a modified Ant Colony Optimization algorithm to identify the optimal composition of the MRAR architecture. Numerical results show that our proposed approach is robust and can significantly reduce the transmission time compared to the conventional star topology. Notably, the reduction in uplink transmission time compared to baseline policies can be substantial in scenarios applicable to large-scale FL, where client devices are densely distributed.