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Byeonghui Jeong - IEEE Xplore Author Profile

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Author details

Byeonghui Jeong

Publications

6

Citations

57

Publications by Year

20222025

Co-Authors:

Seungyeon BaekJueun JeonYoung-Sik JeongSihyun Park

Byeonghui Jeong

Affiliation

Department of Computer Science and Artificial Intelligence

Dongguk University

Seoul, South Korea

Publication Topics

Deep Learning Models,
Long Short-term Memory,
Resource Utilization,
Usage Metrics,
CPU Usage,
Memory Usage,
Resource Costs,
Time Series Prediction,
Worker Nodes,
Average Use,
Bidirectional Long Short-term Memory,
Forecasting

Biography

Byeonghui Jeong received the B.S. degree in computer science and engineering from Kongju National University, Cheonan, Republic of Korea, in 2021, and the M.S. degree in multimedia engineering from Dongguk University, Seoul, Republic of Korea, in 2023, where he is currently pursuing the Ph.D. degree with the Department of Computer Science and Artificial Intelligence.,His current research interests include cloud computing and information security for the Internet of Things.(Based on document published on 3 May 2024).

Publications

6

Citations

57

Publications by Year

20222025

Co-Authors:

Seungyeon Baek
Jueun Jeon
Young-Sik Jeong
Sihyun Park

Author's Published Works

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Byeonghui Jeong(6)
Young-Sik Jeong(6)
Jueun Jeon(5)
Seungyeon Baek(2)
Sihyun Park(1)
Department of Multimedia Engineering, Dongguk University, Seoul, Republic of Korea(3)
Department of Multimedia Engineering, Dongguk University, Seoul, South Korea(2)
Department of AI.SW, Dongguk University, Seoul, Republic of Korea(1)
Department of Computer Science and Artificial Intelligence, Dongguk University, Seoul, Republic of Korea(1)
Department of AI·SW, Dongguk University, Seoul, South Korea(1)
IEEE Access(1)
IEEE Transactions on Cloud Computing(1)
IEEE Transactions on Consumer Electronics(1)
IEEE Transactions on Industrial Informatics(1)
IEEE Transactions on Information Forensics and Security(1)
IEEE(6)
Deep Learning Models(4)
Long Short-term Memory(4)
Resource Utilization(4)
Usage Metrics(4)
Bidirectional Long Short-term Memory(3)

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ARAScaler: Adaptive Resource Autoscaling Scheme Using ETimeMixer for Efficient Cloud-Native Computing

Byeonghui Jeong;Young-Sik Jeong

IEEE Transactions on Services Computing

Year: 2025 | Volume: 18, Issue: 1 | Journal Article |

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The container resource autoscaling techniques offer scalability and continuity for microservices operating in cloud-native computing environments. However, they manage resources inefficiently, causing resource waste and overload under complex workload patterns. In addition, these techniques fail to prevent oscillations caused by dynamic workloads, increasing the operational complexity. Therefore, ...Show More

ARAScaler: Adaptive Resource Autoscaling Scheme Using ETimeMixer for Efficient Cloud-Native Computing

Byeonghui Jeong;Young-Sik Jeong

IEEE Transactions on Services Computing

Year: 2025 | Volume: 18, Issue: 1 | Journal Article |

Efficient Container Scheduling With Hybrid Deep Learning Model for Improved Service Reliability in Cloud Computing

Jueun Jeon;Sihyun Park;Byeonghui Jeong;Young-Sik Jeong

Year: 2024 | Volume: 12 | Journal Article |

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In a cloud computing environment, the container scheduling technique ensures reliability for containerized applications by selecting nodes that satisfy various resource requirements and then deploying containers. If the initial resources of a container are over-allocated, resources may be wasted, or other containers that are waiting in a scheduling queue may not be allocated. However, if resources...Show More

Efficient Container Scheduling With Hybrid Deep Learning Model for Improved Service Reliability in Cloud Computing

Jueun Jeon;Sihyun Park;Byeonghui Jeong;Young-Sik Jeong

Year: 2024 | Volume: 12 | Journal Article |

Static Multi Feature-Based Malware Detection Using Multi SPP-net in Smart IoT Environments

Jueun Jeon;Byeonghui Jeong;Seungyeon Baek;Young-Sik Jeong

IEEE Transactions on Information Forensics and Security

Year: 2024 | Volume: 19 | Journal Article |

Cited by: Papers (8)

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With the steady increase in the demand for Internet of Things (IoT) devices in diverse industries, such as manufacturing, medical care, and transportation infrastructure, the production of malware tailored for Smart IoT environments is also increasing. Accordingly, various malware detection studies are being conducted to detect not only known malware but also variant malware. However, it is diffic...Show More

Static Multi Feature-Based Malware Detection Using Multi SPP-net in Smart IoT Environments

Jueun Jeon;Byeonghui Jeong;Seungyeon Baek;Young-Sik Jeong

IEEE Transactions on Information Forensics and Security

Year: 2024 | Volume: 19 | Journal Article |

Intelligent Resource Scaling for Container-Based Digital Twin Simulation of Consumer Electronics

Jueun Jeon;Byeonghui Jeong;Young-Sik Jeong

IEEE Transactions on Consumer Electronics

Year: 2024 | Volume: 70, Issue: 1 | Journal Article |

Cited by: Papers (8)

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With the advent of Industry 4.0, high-quality consumer electronics are being efficiently produced by simulating a virtual model connected to a physical object using the digital twin (DT) technology. Furthermore, high-performance cloud computing technology is being used to simulate resource-intensive consumer electronics DT. Virtual machine (VM)-based DT simulation can simulate various DTs in paral...Show More

Intelligent Resource Scaling for Container-Based Digital Twin Simulation of Consumer Electronics

Jueun Jeon;Byeonghui Jeong;Young-Sik Jeong

IEEE Transactions on Consumer Electronics

Year: 2024 | Volume: 70, Issue: 1 | Journal Article |

Proactive Resource Autoscaling Scheme Based on SCINet for High-Performance Cloud Computing

Byeonghui Jeong;Jueun Jeon;Young-Sik Jeong

IEEE Transactions on Cloud Computing

Year: 2023 | Volume: 11, Issue: 4 | Journal Article |

Cited by: Papers (7)

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The container resource autoscaling technique provides scalability to cloud services composed of microservice architecture in a cloud-native computing environment. However, the service efficiency is reduced as the scaling is delayed because dynamic loads occur with various workload patterns. Furthermore, estimating the efficient resource size for the workload is difficult, resulting in resource was...Show More

Proactive Resource Autoscaling Scheme Based on SCINet for High-Performance Cloud Computing

Byeonghui Jeong;Jueun Jeon;Young-Sik Jeong

IEEE Transactions on Cloud Computing

Year: 2023 | Volume: 11, Issue: 4 | Journal Article |

Hybrid Malware Detection Based on Bi-LSTM and SPP-Net for Smart IoT

Jueun Jeon;Byeonghui Jeong;Seungyeon Baek;Young-Sik Jeong

IEEE Transactions on Industrial Informatics

Year: 2022 | Volume: 18, Issue: 7 | Journal Article |

Cited by: Papers (34)

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In this article, we propose the hybrid malware detection scheme, HyMalD, with bidirectional long short-term memory (Bi-LSTM) and the spatial pyramid pooling network (SPP-Net). Its purpose is to protect Internet of Things (IoT) devices and minimize the damage caused by infection through obfuscated malware. HyMalD performs the static and dynamic analyses logically simultaneously to detect obfuscated...Show More

Hybrid Malware Detection Based on Bi-LSTM and SPP-Net for Smart IoT

Jueun Jeon;Byeonghui Jeong;Seungyeon Baek;Young-Sik Jeong

IEEE Transactions on Industrial Informatics

Year: 2022 | Volume: 18, Issue: 7 | Journal Article |

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