Machine Learning-Based Bandwidth Prediction for Low-Latency H2M Applications

Ruan, Lihua, Dias, Maluge Pubuduni Imali and Wong, Elaine 2019, Machine Learning-Based Bandwidth Prediction for Low-Latency H2M Applications, IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3743-3752, doi: 10.1109/jiot.2018.2890563.

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Title Machine Learning-Based Bandwidth Prediction for Low-Latency H2M Applications
Author(s) Ruan, Lihua
Dias, Maluge Pubuduni ImaliORCID iD for Dias, Maluge Pubuduni Imali orcid.org/0000-0003-0773-8166
Wong, Elaine
Journal name IEEE Internet of Things Journal
Volume number 6
Issue number 2
Start page 3743
End page 3752
Total pages 10
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Publication date 2019-04
ISSN 2327-4662
2372-2541
Keyword(s) Artificial neural network (ANN)
low latency
machine learning
predictive bandwidth allocation
Language eng
DOI 10.1109/jiot.2018.2890563
Indigenous content off
Field of Research 0805 Distributed Computing
1005 Communications Technologies
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30145008

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