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. Attached Files Name Description MIMEType Size Downloads Title Machine Learning-Based Bandwidth Prediction for Low-Latency H2M Applications Author(s) Ruan, Lihua 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 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 06 Nov 2020, 15:02:39 EST Sat, 07 Nov 2020, 04:00:52 EST Mon, 09 Nov 2020, 07:13:04 EST Mon, 16 Nov 2020, 10:13:39 EST Tue, 17 Nov 2020, 05:04:19 EST Tue, 17 Nov 2020, 08:45:15 EST Tue, 17 Nov 2020, 08:46:47 EST Filtered Full Citation counts:   Cited 6 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 31 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Mon, 16 Nov 2020, 10:13:39 EST

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