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

M. Shamim Hossain; Nadra Guizani; Ammar Rayes; Victor C. M. Leung; Honggang Wang; Cheng-Xiang Wang

doi:10.1109/MNET.2021.9454555

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

M. Shamim Hossain, Nadra Guizani, Ammar Rayes, Victor C. M. Leung, Honggang Wang, Cheng-Xiang Wang

Research output: Contribution to journal › Editorial

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.

Original language	English
Pages (from-to)	12-13
Number of pages	2
Journal	IEEE Network
Volume	35
Issue number	3
DOIs	https://doi.org/10.1109/MNET.2021.9454555
Publication status	Published - May 2021

ASJC Scopus subject areas

Software
Information Systems
Hardware and Architecture
Computer Networks and Communications

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title = "Guest Editorial: AI-Enabled Networking Technologies for Tackling Epidemic Diseases",

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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AU - Guizani, Nadra

AU - Rayes, Ammar

AU - Leung, Victor C. M.

AU - Wang, Honggang

AU - Wang, Cheng-Xiang

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

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