The original Python Testbed for Federated Learning Algorithms is a light FL framework, which provides the three generic algorithms: the centralized federated learning, the decentralized federated learning, and the TDM communication (i.e., peer data exchange) in the current time slot. The limitation of the latter is that it allows communication only between pairs of network nodes. This paper presents the new generic algorithm for the universal TDM communication that overcomes this limitation, such that a node can communicate with an arbitrary number of peers (assuming the peers also want to communicate with it). The paper covers: (i) the algorithm's theoretical foundation, (ii) the system design, and (iii) the system validation. The main advantage of the new algorithm is that it supports real-world TDM communications over inter satellite links.

翻译：原始Python联邦学习算法测试平台是一个轻量级联邦学习框架，提供三种通用算法：集中式联邦学习、去中心化联邦学习以及当前时隙的TDM通信（即对等数据交换）。后者的局限性在于仅允许网络节点对之间进行通信。本文提出了一种新的通用TDM通信算法，克服了这一限制，使得节点可以与任意数量的对等节点进行通信（假设对等节点也愿意与其通信）。本文涵盖：（i）算法的理论基础，（ii）系统设计，以及（iii）系统验证。新算法的主要优势在于支持星间链路上的实际TDM通信。