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Publication Date

Manuscript Submission Deadline

Special Issue

Call for Papers

With the outbreak of the coronavirus COVID-19 pandemic, the whole world has been facing the greatest challenge of the global health crisis. This crisis has put a heavy burden on the network community with regards to unprecedented challenges in terms of massive network data traffic and optimization of resources. 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. 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 the serious threat of this pandemic and alike.

Despite the huge potential of AI-enabled NGN technologies in response to the current global health crises, many challenges still need to be addressed to fight against the pandemic and beyond. This Special Issue (SI) aims to explore recent advances and disseminate state-of-the-art research on AI-enabled networking technologies for combatting epidemic diseases and beyond through promising networking techniques, including new architectures, design, resource optimization and performance models. The topics of interest for this special issue include, but are not limited to:

  • AI-empowered 5G/B5G architecture and framework for epidemic disease handling and beyond
  • Deep learning (DL) based networked applications, techniques and testbeds for COVID-19
  • AI-enabled networking techniques to monitor, track casualties and prevention of COVID-19 and alike
  • AI-driven next-generation networking technologies for epidemic prevention and control
  • AI-centric Mobile Edge Computing (MEC) approach for COVID-19
  • Next-generation networking technologies to support mobile big data fusion to handle epidemic disease and people tracking
  • AI-empowered 5G/B5G architecture, and system for COVID-19 and alike disease diagnosis
  • Explainable AI (XAI) and predictive network data analytics for COVID-19
  • Network traffic prediction and control for COVID-19 in B5G
  • Adversarial attacks, threats, and defenses for DL-enabled COVID-19 detection and prevention
  • Security and privacy for AI-enabled remote learning/working, remote social events, and medical consultation during COVID-19 crisis
  • AI-techniques for screening, tracking and diagnosis of COVID-19 using 5G/B5G

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Paper Submission Guidelines.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the “May 2021/AI-Enabled Networking Technologies for Tackling Epidemic Diseases” topic from the drop-down menu of Topic/Series titles.

Important Dates

Manuscript Submission Deadline: 15 November 2020 (Extended Deadline)
Initial Decision: 31 December 2020
Revised Manuscript Due: 31 January 2021
Final Decision: 28 February 2021
Final Manuscript Due: 31 March 2021
Publication Date: May 2021

Guest Editors

M. Shamim Hossain
King Saud University, Riyadh, Saudi Arabia

Nadra Guizani
Washington State University, USA

Ammar Rayes
Cisco Systems, USA

Victor C.M. Leung
Shenzhen University, China and University of British Columbia, Canada

Honggang Wang
University of Massachusetts Dartmouth, USA

Cheng-Xiang Wang
Southeast University, China & Purple Mountain Laboratories, China