Alhartomi, M.A.; Salh, A.; Audah, L.; Alzahrani, S.; Alzahmi, A.; Altimania, M.R.; Alotaibi, A.; Alsulami, R.; Al-Hartomy, O.
Sustainable Resource Allocation and Reduce Latency Based on Federated-Learning-Enabled Digital Twin in IoT Devices. Sensors 2023, 23, 7262.
https://doi.org/10.3390/s23167262
AMA Style
Alhartomi MA, Salh A, Audah L, Alzahrani S, Alzahmi A, Altimania MR, Alotaibi A, Alsulami R, Al-Hartomy O.
Sustainable Resource Allocation and Reduce Latency Based on Federated-Learning-Enabled Digital Twin in IoT Devices. Sensors. 2023; 23(16):7262.
https://doi.org/10.3390/s23167262
Chicago/Turabian Style
Alhartomi, Mohammed A., Adeeb Salh, Lukman Audah, Saeed Alzahrani, Ahmed Alzahmi, Mohammad R. Altimania, Abdulaziz Alotaibi, Ruwaybih Alsulami, and Omar Al-Hartomy.
2023. "Sustainable Resource Allocation and Reduce Latency Based on Federated-Learning-Enabled Digital Twin in IoT Devices" Sensors 23, no. 16: 7262.
https://doi.org/10.3390/s23167262
APA Style
Alhartomi, M. A., Salh, A., Audah, L., Alzahrani, S., Alzahmi, A., Altimania, M. R., Alotaibi, A., Alsulami, R., & Al-Hartomy, O.
(2023). Sustainable Resource Allocation and Reduce Latency Based on Federated-Learning-Enabled Digital Twin in IoT Devices. Sensors, 23(16), 7262.
https://doi.org/10.3390/s23167262