Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment

عرض إصدارات أخرى (1)

To overcome the three key challenges of federated learning in heterogeneous edge computing, i.e., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Tongxin xuebao
المؤلفون الرئيسيون: Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG
التنسيق: مقال
اللغة:الصينية
منشور في: Editorial Department of Journal on Communications 2023-11-01
الموضوعات:
edge computing
federated learning
Non-IID
heterogeneity
convergence analysis
الوصول للمادة أونلاين:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023196/

الانترنت

http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023196/

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