Rchr
J-GLOBAL ID:201801007650592550
Update date: Jan. 14, 2025
Fukushima Yukinobu
フクシマ ユキノブ | Fukushima Yukinobu
Affiliation and department:
Homepage URL (1):
https://soran.cc.okayama-u.ac.jp/html/6025ed15318681a074506e4da22f6611_ja.html
Research field (1):
Information networks
Research keywords (4):
Optical networking
, Network virtualization
, Edge computing
, Information networks
Research theme for competitive and other funds (8):
- 2023 - 2026 超リアルタイムサービスを指向したネットワーク制御における特徴量エンジニアリン グ
- 2019 - 2023 Construction of a medical information secure management system using ICT and encryption technology
- 2019 - 2023 Construction of a medical information secure management system using ICT and encryption technology
- 2019 - 2022 データセンターネットワークにおけるスループット急落の回避に関する研究
- 2015 - 2018 Development of energy-efficient virtual network mapping technologies
- 2012 - 2015 Power efficient traffic engineering technologies in all-optical networks
- 2010 - 2011 Routing and medium access control technologies in new generation all-optical networks
- 2007 - 2008 Scalable lightpath establishment method for realizing high throughput in next-generation backbone networks
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Papers (54):
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Yukinobu Fukushima, Yuki Koujitani, Kazutoshi Nakane, Yuya Tarutani, Celimuge Wu, Yusheng Ji, Tokumi Yokohira, Tutomu Murase. Deep Reinforcement Learning Enabled Adaptive Virtual Machine Migration Control in Multi-Stage Information Processing Systems. International Journal on Advances in Networks and Services. 2024
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Yuya Tarutani, Taisei Yamamoto, Yukinobu Fukushima, Tokumi Yokohira. A Protection Scheme with Speech Processing against Audio Adversarial Examples. IEEE Access. 2024. 12. 146551-146559
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Yukinobu Fukushima, Yuki Koujitani, Kazutoshi Nakane, Yuya Tarutani, Celimuge Wu, Yusheng Ji, Tokumi Yokohira, Tutomu Murase. Application of a Deep Reinforcement Learning Algorithm to Virtual Machine Migration Control in Multi-Stage Information Processing Systems. in Proceedings of International Conference on Networks (ICN 2024). 2024. 13-18
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Yukinobu Fukushima, Yuta Sagawa, Yuya Tarutani, Tokumi Yokohira. Performance Improvement of a Virtual Network Embedding Algorithm based on Temporal-difference Learning by Resource-Constraint-Aware Candidate Solution Selection. IEIE Transactions on Smart Processing and Computing. 2024. 13. 2. 158-166
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Kazutoshi Nakane, Yukinobu Fukushima, Celimuge Wu, Yusheng Ji, Tutomu Murase. VM Migration that Assures and Maximizes Accuracy in Multi-stage Information Processing Systems. ICCE. 2024. 1-5
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MISC (148):
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中村昂平, 福島行信, 樽谷優弥, 横平徳美. Model Parameter Aggregation Method for Reducing Network Load in Hierarchical Federated Learning. 電子情報通信学会技術研究報告(Web). 2024. 124. 139(IN2024 10-32)
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GAO Sen, 樽谷優弥, 福島行信, 横平徳美. A juvenile leaf growth prediction method using machine learning and image processing. 電子情報通信学会大会講演論文集(CD-ROM). 2024. 2024
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鈴木大補, 樽谷優弥, 福島行信, 横平徳美. Audio Adersarial Example identification method using multiple features. 電子情報通信学会大会講演論文集(CD-ROM). 2024. 2024
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糀谷友貴, 中根和俊, 樽谷優弥, WU Celimuge, JI Yusheng, 横平徳美, 村瀬勉, 福島行信. Application of a Deep Reinforcement Learning Algorithm to Virtual Machine Migration Control in Multi-Stage Information Processing Systems. 電子情報通信学会技術研究報告(Web). 2024. 123. 398(IN2023 65-113)
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梅木勇杜, 中根和俊, 福島行信, WU Celimuge, JI Yusheng, 村瀬勉. VM Migration Control considering Terminal Location in Multi-stage Information Processing System. 電子情報通信学会技術研究報告(Web). 2024. 123. 398(IN2023 65-113)
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Patents (2):
Education (3):
- 2003 - 2006 Osaka University
- 2001 - 2003 Osaka University Graduate School of Engineering Science
- 1997 - 2001 Osaka University
Professional career (1):
Work history (4):
- 2018/02 - 現在 Okayama University
- 2015/04 - 2018/01 Okayama University
- 2007/04 - 2015/03 Okayama University The Graduate School of Natural Science and Technology
- 2006/04 - 2007/03 岡山大学 大学院自然科学研究科産業創成工学専攻 助手
Awards (2):
- 2024/05 - ICN2024 Best Paper Award Application of a Deep Reinforcement Learning Algorithm to Virtual Machine Migration Control in Multi-Stage Information Processing Systems
- 2024/02 - 電子情報通信学会情報ネットワーク研究会 情報ネットワーク研究会優秀発表賞 多段階情報処理システムにおけるVM移動制御への深層強化学習の適用
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