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Won-Joo Hwang

Researcher at Pusan National University

Publications -  191
Citations -  2975

Won-Joo Hwang is an academic researcher from Pusan National University. The author has contributed to research in topics: Wireless network & Throughput. The author has an hindex of 20, co-authored 174 publications receiving 1637 citations. Previous affiliations of Won-Joo Hwang include Inje University & University of Technology, Sydney.

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A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art.

TL;DR: In this article, the authors provide a comprehensive overview of mobile edge computing (MEC) and its potential use cases and applications, as well as discuss challenges and potential future directions for MEC research.
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A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

TL;DR: This survey provides a holistic overview of MEC technology and its potential use cases and applications, and outlines up-to-date researches on the integration of M EC with the new technologies that will be deployed in 5G and beyond.
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Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research

TL;DR: In this paper, the authors provide a comprehensive survey of the current developments towards 6G and elaborate the requirements that are necessary to realize the 6G applications, and summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions toward 6G.
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Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

TL;DR: An overview of AI and big data, then identify the applications aimed at fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the CO VID-19 situation.
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Whale Optimization Algorithm With Applications to Resource Allocation in Wireless Networks

TL;DR: This article presents the fundamental backgrounds and the binary version of the WOA as well as introducing a penalty method to handle optimization constraints and presents the adoption of WOA to solve a variety of potential resource allocation problems in 5G wireless networks and beyond.