Energy-Efficient Federated Learning With Resource Allocation for Green IoT Edge Intelligence in B5G

• Main Authors: ADEB SALH, ADEB SALH, RAZALI NGAH, RAZALI NGAH, LUKMAN AUDAH, LUKMAN AUDAH, QAZWAN ABDULLAH, QAZWAN ABDULLAH, YAHYA M. AL-MOLIK, YAHYA M. AL-MOLIK, KHALED A. ALJALOUD, KHALED A. ALJALOUD, HAIRUL NIZAM TALIB, HAIRUL NIZAM TALIB
• Format: Article
• Language: English
• Published: Ieee Acces 2023
• Subjects: T Technology (General)
• Online Access: http://eprints.uthm.edu.my/11455/1/J15916_cf78dab738eabff1c909c88fd9243b22.pdf; http://eprints.uthm.edu.my/11455/; https://doi.org/10.1109/ACCESS.2023.3244099

An edge intelligence-aided Internet-of-Things (IoT) network has been proposed to accelerate the response of IoT services by deploying edge intelligence near IoT devices. The transmission of data from IoT devices to the edge nodes leads to large network traffic in the wireless connections. Federated...