Achieving low-latency human-to-machine (H2M) applications: an understanding of H2M traffic for AI-facilitated bandwidth allocation

Ruan, Lihua, Dias, Maluge Pubuduni Imali and Wong, Elaine 2021, Achieving low-latency human-to-machine (H2M) applications: an understanding of H2M traffic for AI-facilitated bandwidth allocation, IEEE Internet of Things journal, vol. 8, no. 1, pp. 626-635, doi: 10.1109/jiot.2020.3007947.

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Title Achieving low-latency human-to-machine (H2M) applications: an understanding of H2M traffic for AI-facilitated bandwidth allocation
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 8
Issue number 1
Start page 626
End page 635
Total pages 10
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Publication date 2021-01-01
ISSN 2372-2541
Keyword(s) bandwidth allocation scheme
haptic communication
human-to-machine applications
low latency
tactile Internet
Language eng
DOI 10.1109/jiot.2020.3007947
Indigenous content off
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30145007

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