Guest Editors
Dr. Hwa-Young Jeong
Email: hyjeong@khu.ac.kr
Affiliation: Humanitas College, Kyung Hee University, 02447, Seoul, Republic of Korea
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Research Interests: software engineering, IoT, intelligent IoT, machine learning, deep learning, machine learning, multimedia system, e-learning system
Dr. Jason C. Hung
Email: jhung@gm.nutc.edu.tw
Affiliation: Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, 404, Taichung City, Taiwan
Homepage:
Research Interests: e-learning, intelligent system, social computing, affective computing, multimedia system, artificial intelligence
Dr. Yen Neil Yuwen
Email: neilyyen@u-aizu.ac.jp
Affiliation: School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, 965-8580, Japan
Homepage:
Research Interests: human-centered computing computational intelligence, human modeling, data mining, machine learning, social web, cognitive science, awareness engineering
Summary
Recently, IoT applications such as smart homes, autonomous vehicles, smart agriculture, and smart healthcare have improved the quality of people's lives. As this technical trends, the emerging distributed computing paradigm of "fog computing" and "edge computing," which is an extension of cloud computing, has gained attention from the industrial and research communities. Also as the use of IoT and machine learning (ML) increases, the workload on the cloud and fog/edge becomes increasingly diverse and dynamic.
There are many active research projects being conducted on applications in cloud-fog, fog-edge, and cloud-edge computing environments. This special issue welcomes application or demonstration studies in fields such as IoT, digital twin, sensor networks, smart healthcare, environmental engineering, and security within these cloud-fog, fog-edge, and cloud-edge computing environments. Potential topics include but are not limited to:
· Cloud-Fog-Edge-based Digital Twin Network
· Healthcare Applications with Fog-Edge-Cloud Computing
· Deep Learning in Fog-Cloud Computing Environments
· Multi-dimensional Industrial IoT (IIoT) Data in Cloud-Fog or Fog-Edge Network
· Security in Cloud-Fog-Edge Computing
· Detecting Attacks in Fog and Cloud Computing Environments
· Intelligent Sensor Networks for Cloud-Fog-Edge Computing
· Blockchain for Secure Cloud-Fog-Edge Computing
· Anomaly Detection in Cloud-Fog-Edge Environments
· Integration Frameworks for Cloud-Fog-Edge Computing
Keywords
Digital Twin, healthcare with cloud-fog computing, fog-edge computing, cloud-edge computing, integration for cloud, fog, and edge computing, cloud-fog or fog-edge network
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