Choong Seon Hong

Research interests

Publications

• Digital-Twin-Enabled 6G: Vision, Architectural Trends, and Future Directions

  IEEE Communications Magazine · 2022 · https://doi.org/10.1109/mcom.001.21143

• Digital Twin of Wireless Systems: Overview, Taxonomy, Challenges, and Opportunities

  IEEE Communications Surveys & Tutorials · 2022 · https://doi.org/10.1109/comst.2022.3198273

• On the Optimality of Reconfigurable Intelligent Surfaces (RISs): Passive Beamforming, Modulation, and Resource Allocation

  IEEE Transactions on Wireless Communications · 2021 · 10.1109/twc.2021.3058366

• Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

  IEEE Communications Surveys & Tutorials · 2021 · 10.1109/comst.2021.3090430

• Blockchain for IoT-based smart cities: Recent advances, requirements, and future challenges

  Journal of Network and Computer Applications · 2021 · 10.1016/j.jnca.2021.103007

• An Incentive Mechanism for Federated Learning in Wireless Cellular Networks: An Auction Approach

  IEEE Transactions on Wireless Communications · 2021 · 10.1109/twc.2021.3062708

• Edge-Computing-Enabled Smart Cities: A Comprehensive Survey

  IEEE Internet of Things Journal · 2020 · 10.1109/jiot.2020.2987070

• Coexistence Mechanism Between eMBB and uRLLC in 5G Wireless Networks

  IEEE Transactions on Communications · 2020 · 10.1109/tcomm.2020.3040307

• 6G Wireless Systems: A Vision, Architectural Elements, and Future Directions

  IEEE Access · 2020 · 10.1109/access.2020.3015289

• Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges

  IEEE Access · 2020 · 10.1109/access.2020.2975072

• Energy Efficient Federated Learning Over Wireless Communication Networks

  IEEE Transactions on Wireless Communications · 2020 · https://doi.org/10.1109/twc.2020.3037554

• A Crowdsourcing Framework for On-Device Federated Learning

  IEEE Transactions on Wireless Communications · 2020 · 10.1109/twc.2020.2971981

• Deep Learning Based Caching for Self-Driving Cars in Multi-Access Edge Computing

  IEEE Transactions on Intelligent Transportation Systems · 2020 · 10.1109/tits.2020.2976572

• Energy-Efficient Resource Management in UAV-Assisted Mobile Edge Computing

  IEEE Communications Letters · 2020 · 10.1109/lcomm.2020.3026033

• Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism

  IEEE Communications Magazine · 2020 · 10.1109/mcom.001.1900649

• FLchain: Federated Learning via MEC-enabled Blockchain Network

  · 2019 · 10.23919/apnoms.2019.8892848

• Joint Communication, Computation, Caching, and Control in Big Data Multi-Access Edge Computing

  IEEE Transactions on Mobile Computing · 2019 · 10.1109/tmc.2019.2908403

• Autonomous Driving Cars in Smart Cities: Recent Advances, Requirements, and Challenges

  IEEE Network · 2019 · 10.1109/mnet.2019.1900120

• Federated Learning over Wireless Networks: Optimization Model Design and Analysis

  Journal · 2019 · https://doi.org/10.1109/infocom.2019.8737464

• eMBB-URLLC Resource Slicing: A Risk-Sensitive Approach

  IEEE Communications Letters · 2019 · 10.1109/lcomm.2019.2900044

• Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges

  Future Generation Computer Systems · 2018 · https://doi.org/10.1016/j.future.2018.09.058

• Game Theory for Cyber Security and Privacy

  ACM Computing Surveys · 2017 · 10.1145/3057268

• Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience

  IEEE Journal on Selected Areas in Communications · 2017 · https://doi.org/10.1109/jsac.2017.2680898

• Traffic-Aware and Energy-Efficient vNF Placement for Service Chaining: Joint Sampling and Matching Approach

  IEEE Transactions on Services Computing · 2017 · 10.1109/tsc.2017.2671867

• Human Behavior Analysis by Means of Multimodal Context Mining

  Sensors · 2016 · https://doi.org/10.3390/s16081264

Current projects

No projects listed.