Communications and Networking
Federated Learning for Wireless Networks:
- Research Objective: We aim to develop novel and innovative federated learning architectures and explore the potential of federated learning for privacy-preserved wireless networks.
- Team leader: Dinh C. Nguyen and Pubudu N. Pathirana
- Collaborators: Prof. H. Vincent Poor (Princeton University, USA), Prof. Dusit Niyato (Nanyang Technological University, Singapore), Prof. Octavia Dobre (Memorial University, Canada), Prof. Albert Y. Zomaya (University of Sydney), Prof. Aruna Seneviratne (University of New South Wales, Sydney), Dr. Ming Ding (Data61 CSIRO, Sydney).
- Selected Publications:
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Jun Li, and H. Vincent Poor, “Federated Learning for Internet of Things: A Comprehensive Survey”, IEEE Communications Surveys and Tutorials, pp.1-38, May 2021. (Q1, Impact Factor-IF: 25.4)
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, and H. Vincent Poor, “Federated Learning for Industrial Internet of Things in Future Industries”, IEEE Wireless Communications Magazine, Apr. 2021. (Q1, IF: 11.4)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Albert Y. Zomaya, “Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing”, IEEE Internet of Things Journal, Sept. 2021. (Q1, IF:9.5)
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Dinh C. Nguyen, Ming Ding, Q.-V. Pham, Pubudu N. Pathirana, L. B. Le, Aruna Seneviratne, Jun Li, Dusit Niyato, and H. Vincent Poor, “Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges”, IEEE Internet of Things Journal, Apr. 2021. (Q1, IF: 9.9)
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Blockchain for Internet of Things:
- Research Objective: We aim to develop novel blockchain-based solutions for secure Internet of Things, such as blockchain for access control, blockchain for user authentication, and blockchain for secure edge computing in Internet of Things.
- Team leader: Dinh C. Nguyen and Pubudu N. Pathirana
- Collaborators: Prof. H. Vincent Poor (Princeton University, USA), Prof. Aruna Seneviratne (University of New South Wales, Sydney), Dr. Ming Ding (Data61 CSIRO, Sydney).
- Selected Publications:
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Integration of Blockchain and Cloud of Things: Architecture, Applications and Challenges”, IEEE Communications Surveys and Tutorials, vol. 4, pp. 2521-2549, Aug. 2020. (Q1, IF: 25.3)
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, and H. Vincent Poor, “Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing: A Multi-agent Deep Reinforcement Learning Approach”, IEEE Transactions on Mobile Computing, Sept. 2021. (Q1, IF:5.6)
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, “Secure Computation Offloading in Blockchain based IoT Networks with Deep Reinforcement Learning”, IEEE Transactions on Network Science and Engineering, pp. 1-16, Aug. 2021. (Q1, IF:3.9)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, “BEdgeHealth: A Decentralized Architecture for Edge-based IoMT Networks Using Blockchain”, IEEE Internet of Things Journal, pp.1-14, Feb. 2021. (Q1, IF: 9.9)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Privacy-Preserved Task Offloading in Mobile Blockchain with Deep Reinforcement Learning”, IEEE Transactions on Network and Service Management, vol. 17, pp. 2536-2549, Aug. 2020. (Q1, IF:4.2)
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Dinh C. Nguyen, Pathirana PN, Ming Ding, and Seneviratne Aruna “Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems”, IEEE Access, vol. 7, pp. 66792 – 66806, May 2019. (Q1, IF:3.8)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “A Cooperative Architecture of Data Offloading and Sharing for Smart Healthcare with Blockchain” in the 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2021), Sydney, Jun. 2021.
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Jun Li, and H. Vincent Poor, “Utility Optimization for Blockchain Empowered Edge Computing with Deep Reinforcement Learning”, in the IEEE International Conference on Communications (ICC), Canada, Jun. 2021.
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Blockchain and Edge Computing for Decentralized EMRs Sharing in Federated Healthcare”, in the IEEE Global Communications Conference (GLOBECOM), Taiwan, pp. 1-6, Dec. 2020.
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Dinh C. Nguyen, Khoa Dinh Nguyen, and P. N. Pathirana, “A mobile cloud based IoMT framework for automated health assessment and management,” in 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Berlin, Germany , July 23-27, 2019.
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Edge Intelligence for Wireless Communications and Networking
- Research Objective: We aim to create new edge intelligence solutions enabled by the convergence of deep learning and edge computing for enabling intelligent and low-latency wireless communications and networking.
- Team leader: Dinh C. Nguyen and Pubudu N. Pathirana
- Collaborators: Prof. H. Vincent Poor (Princeton University, USA), Dr. David Lopez-Perez (Nokia Lab Bells, Spain), Prof. Yonghui Li, University of Sydney (University of Sydney), Prof. Aruna Seneviratne (University of New South Wales, Sydney), Dr. Ming Ding (Data61 CSIRO, Sydney).
- Selected Publications:
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Dinh C. Nguyen, Peng Cheng, Ming Ding, David Lopez-Perez, Pubudu N. Pathirana, Jun Li, Aruna Seneviratne, Yonghui Li, and H. Vincent Poor, “Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective”, IEEE Communications Surveys and Tutorials, pp. 1-1, Sept. 2020. (Q1, IF: 23.7)
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, and H. Vincent Poor, “Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing: A Multi-agent Deep Reinforcement Learning Approach”, IEEE Transactions on Mobile Computing, Sept. 2021. (Q1, IF:5.6)
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, “Secure Computation Offloading in Blockchain based IoT Networks with Deep Reinforcement Learning”, IEEE Transactions on Network Science and Engineering, pp. 1-16, Aug. 2021. (Q1, IF:3.9)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Privacy-Preserved Task Offloading in Mobile Blockchain with Deep Reinforcement Learning”, IEEE Transactions on Network and Service Management, vol. 17, pp. 2536-2549, Aug. 2020. (Q1, IF:4.2)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Deep Reinforcement Learning for Collaborative Offloading in Heterogeneous Edge Networks”, in the 21st IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid 2021), Melbourne, Jan. 2021.
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Jun Li, and H. Vincent Poor, “Utility Optimization for Blockchain Empowered Edge Computing with Deep Reinforcement Learning”, in the IEEE International Conference on Communications (ICC), Canada, Jun. 2021.
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Future Wireless Communications with 5G/6G
- Research Objective: We explore the next generation of wireless communication networks with 5G/6G that are envisioned to revolutionize customer services and applications via the Internet-of-Things towards a future of fully intelligent and autonomous systems.
- Team leader: Dinh C. Nguyen and Pubudu N. Pathirana
- Collaborators: Prof. H. Vincent Poor (Princeton University, USA), Prof. Dusit Niyato (Nanyang Technological University, Singapore), Prof. Octavia Dobre (Memorial University, Canada), Prof. Aruna Seneviratne (University of New South Wales, Sydney), Dr. Ming Ding (Data61 CSIRO, Sydney).
- Selected Publications:
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Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, Octavia Dobre, and H. Vincent Poor, “6G Internet of Things: A Comprehensive Survey”, IEEE Internet of Things Journal, Aug. 2021. (Q1, IF: 9.9)
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Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, and Aruna Seneviratne, “Blockchain for 5G and Beyond Networks: A State of the Art Survey”, Journal of Network and Computer Applications, pp.1-45, May 2020. (Q1, IF: 6.3)
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