Guest Editorial: AI-Enabled Networking Technologies for Tackling Epidemic Diseases

Authors: Hossain, M. Shamim;

Guizani, Nadra;

Rayes, Ammar;

Leung, Victor C. M.;

Wang, Honggang;

Wang, Cheng-Xiang

Source: IEEE Network

Full text

: https://doi.org/10.1109/MNET.2021.9454555

Abstract

With the outbreak of the coronavirus COVID-19 pandemic, the whole world has been facing the greatest challenge of a global health crisis. This crisis puts a heavy burden on the network community with regards to unprecedented challenges such as massive network data traffic and resource optimization. The next-generation networking (NGN) technologies (5G, B5G, and the upcoming 6G) driven by artificial intelligence (AI) and machine learning (ML) has the potential to address these challenges by providing powerful computational processing, ultra-massive machine-type communications with ultra-low latency along with a very high bitrate. The AI algorithms/techniques have huge potential for handling the massive volume of pandemic data, predicting the live pandemic crisis and initiating new research directions to have better network insights to tackle serious threats that effect the global community.

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Hossain, M., Guizani, N., Rayes, A., Leung, V., Wang, H. & Wang, C. 2021, 'Guest Editorial: AI-Enabled Networking Technologies for Tackling Epidemic Diseases', IEEE Network, 35(3), pp. 12-13. https://doi.org/10.1109/MNET.2021.9454555

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DOI: https://doi.org/10.1109/MNET.2021.9454555

Repository URI: https://researchportal.hw.ac.uk/en/publications/7d799959-050d-4030-8c13-64a910b41895