Latency Minimization for TDMA-Based Wireless Federated Learning Networks

Wireless federated learning (FL) is a new distributed machine learning framework that trains a global model through user collaboration over wireless networks. However, the resource heterogeneity of different users greatly impacts on the performance of wireless FL networks. To tackle this challenge,...

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Vydáno v:	IEEE transactions on vehicular technology Ročník 73; číslo 9; s. 13974 - 13979
Hlavní autor:	Xu, Ding
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.09.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Computational geometry Computational modeling Constraints Convexity Data models Energy consumption Federated learning Heterogeneity latency minimization Machine learning Network latency Optimization resource heterogeneity Resource management Scheduling Time Division Multiple Access Time-frequency analysis Training Wireless communication Wireless federated learning Wireless networks
ISSN:	0018-9545, 1939-9359
On-line přístup:	Získat plný text
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