期刊
IEEE COMMUNICATIONS MAGAZINE
卷 58, 期 10, 页码 88-93出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.001.1900649
关键词
-
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIT) [2020R1A4A1018607]
Recent years have witnessed a rapid proliferation of smart Internet of Things (IoT) devices. IoT devices with intelligence require the use of effective machine learning paradigms. Federated learning can be a promising solution for enabling IoT-based smart applications. In this article, we present the primary design aspects for enabling federated learning at the network edge. We model the incentive-based interaction between a global server and participating devices for federated learning via a Stackelberg game to motivate the participation of the devices in the federated learning process. We present several open research challenges with their possible solutions. Finally, we provide an outlook on future research.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据