Joint Coding and Scheduling Optimization for Distributed Learning Over Wireless Edge Networks

Unlike theoretical analysis of distributed learning (DL) in the literature, DL over wireless edge networks faces the inherent dynamics/uncertainty of wireless connections and edge nodes, making DL less efficient or even inapplicable under the highly dynamic wireless edge networks. This article addre...

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Veröffentlicht in:	IEEE journal on selected areas in communications 2022-02, Vol.40 (2), p.484-498
Hauptverfasser:	Van Huynh, Nguyen, Hoang, Dinh Thai, Nguyen, Diep N., Dutkiewicz, Eryk
Format:	Artikel
Sprache:	eng
Schlagworte:	Academic degrees Algorithms Coded computing Codes Coding Cognitive tasks Computer aided instruction Computer architecture deep dueling neural network Deep learning deep reinforcement learning Distance learning distributed learning Edge computing Encoding Machine learning Markov processes Neural networks Nodes Optimization Redundancy reinforcement learning Scheduling Servers Service introduction Task analysis Uncertainty Wireless communication wireless edge networks Wireless networks
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