| Machine learning-based method for prediction of virtual network function resource demands HG Kim, DY Lee, SY Jeong, H Choi, JH Yoo, JWK Hong 2019 IEEE conference on network softwarization (NetSoft), 405-413, 2019 | 58 | 2019 |
| Predicting vnf deployment decisions under dynamically changing network conditions S Lange, HG Kim, SY Jeong, H Choi, JH Yoo, JWK Hong 2019 15th International Conference on Network and Service Management (CNSM), 1-9, 2019 | 35 | 2019 |
| Machine learning-based prediction of VNF deployment decisions in dynamic networks S Lange, HG Kim, SY Jeong, H Choi, JH Yoo, JWK Hong 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS), 1-6, 2019 | 30 | 2019 |
| A network intelligence architecture for efficient vnf lifecycle management S Lange, N Van Tu, SY Jeong, DY Lee, HG Kim, J Hong, JH Yoo, ... IEEE Transactions on Network and Service Management 18 (2), 1476-1490, 2020 | 29 | 2020 |
| Graph neural network based service function chaining for automatic network control DN Heo, S Lange, HG Kim, H Choi 2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS …, 2020 | 25 | 2020 |
| Machine learning based link state aware service function chaining S Jeong, H Kim, JH Yoo, JWK Hong 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS), 1-4, 2019 | 19 | 2019 |
| Machine learning-based optimal vnf deployment S Park, HG Kim, J Hong, S Lange, JH Yoo, JWK Hong 2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS …, 2020 | 18 | 2020 |
| A deep learning approach to vnf resource prediction using correlation between vnfs HG Kim, SY Jeong, DY Lee, H Choi, JH Yoo, JWK Hong 2019 IEEE Conference on Network Softwarization (NetSoft), 444-449, 2019 | 18 | 2019 |
| Graph neural network-based virtual network function deployment prediction HG Kim, S Park, D Heo, S Lange, H Choi, JH Yoo, JWK Hong 2020 16th International Conference on Network and Service Management (CNSM), 1-7, 2020 | 12 | 2020 |
| Blockchain explorer based on RPC-based monitoring system C Lee, H Kim, S Maharjan, K Ko, JWK Hong 2019 IEEE international conference on blockchain and cryptocurrency (ICBC …, 2019 | 11 | 2019 |
| Graph neural network‐based virtual network function deployment optimization HG Kim, S Park, S Lange, D Lee, D Heo, H Choi, JH Yoo, JWK Hong International Journal of Network Management 31 (6), e2164, 2021 | 9 | 2021 |
| Reinforcement learning of graph neural networks for service function chaining DN Heo, D Lee, HG Kim, S Park, H Choi arXiv preprint arXiv:2011.08406, 2020 | 8 | 2020 |
| Graph neural network-based virtual network function management HG Kim, S Park, S Lange, D Lee, D Heo, H Choi, JH Yoo, JWK Hong 2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS …, 2020 | 8 | 2020 |
| Network traffic prediction and auto-scaling of sfc using temporal fusion transformer M Choi, HG Kim, JH Yoo, JWK Hong 2023 24st Asia-Pacific Network Operations and Management Symposium (APNOMS …, 2023 | 1 | 2023 |
| Updating VNF deployment with Scaling Actions using Reinforcement Algorithms N Seo, DN Heo, J Hong, HG Kim, JH Yoo, JWK Hong, H Choi 2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS), 1-4, 2022 | 1 | 2022 |
| AI-based Network Function Virtualization Orchestration HG Kim, JH Yoo, JWK Hong NOMS 2024-2024 IEEE Network Operations and Management Symposium, 1-5, 2024 | | 2024 |
| S-Witch: Switch Configuration Assistant with LLM and Prompt Engineering ED Jeong, HG Kim, S Nam, JH Yoo, JWK Hong NOMS 2024-2024 IEEE Network Operations and Management Symposium, 1-7, 2024 | | 2024 |
| Reinforcement Learning of Graph Neural Networks for Service Function Chaining in Computer Network Management DN Heo, D Lee, HG Kim, S Park, H Choi 2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS), 1-6, 2022 | | 2022 |
| Method and apparatus for graph neural network based virtual network management WK Hong, JH Yoo, HG Kim US Patent App. 17/685,301, 2022 | | 2022 |
| Method of predicting demand of virtual network function resources to which machine learning is applied WK Hong, JH Yoo, HG Kim US Patent 11,341,372, 2022 | | 2022 |
