D2D-Enabled Data Sharing for Distributed Machine Learning at Wireless Network Edge

28 Jan 2020Xiaoran CaiXiaopeng MoJunyang ChenJie Xu

Mobile edge learning is an emerging technique that enables distributed edge devices to collaborate in training shared machine learning models by exploiting their local data samples and communication and computation resources. To deal with the straggler dilemma issue faced in this technique, this paper proposes a new device to device enabled data sharing approach, in which different edge devices share their data samples among each other over communication links, in order to properly adjust their computation loads for increasing the training speed... (read more)

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