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2017 年度 実績報告書

Study of Joint Optimization of Quality of Service/Experience and Security for Differentiated Services in 5G Heterogeneous Networks

研究課題

研究課題/領域番号 16H05858
研究機関東北大学

研究代表者

Fadlullah Zubair  東北大学, 情報科学研究科, 准教授 (40614011)

研究期間 (年度) 2016-04-01 – 2019-03-31
キーワードQoS / QoE / Security / 5G / IoT / ネットワーク / wireless network / security
研究実績の概要

I used game theory to address the tradeoff of QoS and security in the next generation wireless networks. Particularly for the 4G and beyond 4G networks, the tradeoff issue between QoS and security in terms of throughput, delay, encryption/decryption, authentication, and so forth were taken into consideration. The problem was formally constructed using a game-based model by arguing that a model couldn't be constructed to trivially apply conventional optimization methods. Both mobility and fixed scenarios were considered and simulations were conducted showing the effectiveness of the game based method. We then extended our research to other next generation network such as IoT where QoS and security optimization is also critical.
In this fiscal year, we examined the algorithm from multiple approaches and improved the proposed method.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

As with last year, I have used game theory to integrate security and QoS. However, from the recent breakthrough in deep learning, I am studying how to improve the network QoS aspect more by training using large network datasets with the aid of deep learning techniques.

今後の研究の推進方策

Now I am studying the 5G network architecture. In the future, particular focus will be given on ultra dense network or UDN where beamforming and massive MIMO technologies are used. Using traditional FDD or TDD, such technologies are prone to resource allocation problems. I am planning to using deep learning, which is the state-of-the-art machine learning / Artificial Intelligence (AI) technique, to plan for intelligent resource control for mobile users in 5G UDNs to alleviate potential congestion and support next generation services and applications. After the resource allocation based QoS and QoE implementation, security integration focus with deep learning will also be taken into account.

  • 研究成果

    (8件)

すべて 2018 2017

すべて 雑誌論文 (7件) (うち国際共著 1件、 査読あり 7件) 学会発表 (1件) (うち国際学会 1件)

  • [雑誌論文] On A Novel Adaptive UAV-Mounted Cloudlet-Aided Recommendation System for LBSNs2018

    • 著者名/発表者名
      Fengxiao Tang, Zubair Md. Fadlullah, Bomin Mao, Nei Kato, Fumie Ono, and Ryu Miura
    • 雑誌名

      IEEE Transactions on Emerging Topics in Computing

      巻: - ページ: 1-13

    • DOI

      10.1109/TETC.2018.2792051

    • 査読あり
  • [雑誌論文] Characterizing Flow, Application, and User Behavior in Mobile Networks: A Framework for Mobile Big Data2018

    • 著者名/発表者名
      Yuanyuan Qiao, Zhizhuang Xing, Zubair Md. Fadlullah, Jie Yang, and Nei Kato
    • 雑誌名

      IEEE Wireless Communications

      巻: 25 ページ: 40-49

    • DOI

      10.1109/MWC.2018.1700186

    • 査読あり / 国際共著
  • [雑誌論文] Multi-Hop Wireless Transmission in Multi-Band WLAN Systems: Proposal and Future Perspective2017

    • 著者名/発表者名
      Zubair Md. Fadlullah, Yuichi Kawamoto, Hiroki Nishiyama, Nei Kato, Naoto Egashira, Kazuto Yano, and Tomoaki Kumagai
    • 雑誌名

      IEEE Wireless Communications

      巻: 26 ページ: 108-113

    • DOI

      10.1109/MWC.2017.1700148

    • 査読あり
  • [雑誌論文] AC-POCA: Anti-Coordination Game based Partially Overlapping Channels Assignment in Combined UAV and D2D based Networks2017

    • 著者名/発表者名
      Fengxiao Tang, Zubair Md. Fadlullah, Nei Kato, Fumie Ono, and Ryu Miura
    • 雑誌名

      IEEE Transactions on Vehicular Technology

      巻: 67 ページ: 1672-1683

    • DOI

      10.1109/TVT.2017.2753280

    • 査読あり
  • [雑誌論文] On Removing Routing Protocol from Future Wireless Networks: A Real-time Deep Learning Approach for Intelligent Traffic Control2017

    • 著者名/発表者名
      Fengxiao Tang, Bomin Mao, Zubair Md. Fadlullah, Nei Kato, Osamu Akashi, Takeru Inoue, and Kimihiro Mizutani,
    • 雑誌名

      IEEE Wireless Communications

      巻: 25 ページ: 154-160

    • DOI

      10.1109/MWC.2017.1700244

    • 査読あり
  • [雑誌論文] Routing or Computing? The Paradigm Shift Towards Intelligent Computer Network Packet Transmission Based on Deep Learning2017

    • 著者名/発表者名
      Bomin Mao, Zubair Md. Fadlullah, Fengxiao Tang, Nei Kato, Osamu Akashi, Takeru Inoue, and Kimihiro Mizutani
    • 雑誌名

      IEEE Transactions on Computers

      巻: 66 ページ: 1946-1960

    • DOI

      10.1109/TC.2017.2709742

    • 査読あり
  • [雑誌論文] State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems2017

    • 著者名/発表者名
      Zubair Md. Fadlullah, Fengxiao Tang, Bomin Mao, Nei Kato, Osamu Akashi, Takeru Inoue, and Kimihiro Mizutani
    • 雑誌名

      IEEE Communications Surveys & Tutorials

      巻: 19 ページ: 2432-2455

    • DOI

      10.1109/COMST.2017.2707140

    • 査読あり
  • [学会発表] A Tensor Based Deep Learning Technique for Intelligent Packet Routing2017

    • 著者名/発表者名
      Bomin Mao, Zubair Md. Fadlullah, Fengxiao Tang, Nei Kato, Osamu Akashi, Takeru Inoue, and Kimihiro Mizutani
    • 学会等名
      IEEE Global Communications Conference (GLOBECOM 2017)
    • 国際学会

URL: 

公開日: 2019-12-27  

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