In recent years, as the boundaries of computing have expanded with the emergence of the Internet of Things (IoT) and its increasing number of devices continuously producing flows of data, it has become paramount to boost speed and to reduce latency. Recent approaches to this growing complexity and data deluge aim to integrate seamlessly and securely diverse computing tiers and data environments, spanning from core cloud to edge — the Computing Continuum (or Edge-to-Cloud Continuum). Typically, the cloud is used for resource-intensive computations while the edge for low-latency tasks.

中文翻译：

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在整个计算连续体中实现联邦学习：系统、挑战和未来方向


近年来，随着物联网 (IoT) 的出现以及不断产生数据流的设备数量不断增加，计算的边界不断扩大，提高速度和减少延迟变得至关重要。针对这种日益增长的复杂性和数据洪流的最新方法旨在无缝且安全地集成不同的计算层和数据环境，涵盖从核心云到边缘的计算连续体（或边缘到云连续体）。通常，云用于资源密集型计算，而边缘用于低延迟任务。