Tiffany Ying He

PhD, IEEE Member
Senior Research Associate & Adjunct Assistant Professor, School of Information Technology
Program Coordinator, NSERC CREATE Program for Building Trust in Connected and Autonomous Vehicles (TrustCAV)
Carleton University

Publications

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      Journal Papers

      1. Y. He, Y. Wang, C. Qiu, Q. Lin, J. Li, and Z. Ming, ``Blockchain-based Edge Computing Resource Allocation in IoT: A Deep Reinforcement Learning Approach," IEEE Internet of Things Journal, vol. 8, no. 4, pp. 2226-2237, Feb. 2021.
      2. Y. He, Y. Wang, F. Richard Yu, Q. Lin, J. Li, and Victor C.M. Leung, ``Efficient Resource Allocation for Multi-Beam Satellite-Terrestrial Vehicular Networks: A Multi-Agent Actor-Critic Method With Attention Mechanism," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2727-2738, Mar. 2022.
      3. Y. He, Y. Wang, Q. Lin and J. Li, ``Meta-Hierarchical Reinforcement Learning (MHRL)-Based Dynamic Resource Allocation for Dynamic Vehicular Networks," IEEE Transactions on Vehicular Technology, vol. 71, no. 4, pp. 3495-3506, Apr. 2022.
      4. Y. He, K. Huang, G. Zhang, F. Richard Yu, J. Chen, and J. Li, ``Bift: A Blockchain-Based Federated Learning System for Connected and Autonomous Vehicles," IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12311-12322, Jul. 2022.
      5. L. Chen, Y. He, Q. Wang, W. Pan, and Z. Ming, ``Joint Optimization of Sensing, Decision-making and Motion-controlling for Autonomous Vehicles: A Deep Reinforcement Learning Approach," IEEE Transactions on Vehicular Technology, vol. 71, vol. 5, pp. 4642-4654, May 2022.
      6. Y. He, H. Wang, Y. Li, K. Huang, Victor C.M. Leung, F. Richard Yu, and Z. Ming, ``An Efficient Ciphertext-Policy Attribute-Based Encryption Scheme Supporting Collaborative Decryption with Blockchain," IEEE Internet of Things Journal, vol. 9, no. 4, pp. 2722-2733, Feb. 2022.
      7. N. Chakraborty, Y. Chao, J. Li, S. Mishra, C. Luo, Y. He, and J. Chen, ``RTT-Based Rogue UAV Detection in IoV Networks," IEEE Internet of Things Journal, vol. 9, no. 8, pp. 5909-5919, Apr. 2022.
      8. Z. Liu, J. Li, C. Wang, F. Richard Yu, J. Chen, Y. He, and C. Sun, ``System Identification Based on Generalized Orthonormal Basis Function for Unmanned Helicopters: A Reinforcement Learning Approach," IEEE Transactions on Vehicular Technology, vol. 70, no. 2, pp. 1135-1145, Feb. 2021.
      9. Y. He, C. Liang, F. Richard Yu, and Z. Han, ``Trust-based Social Networks with Computing, Caching and Communications: A Deep Reinforcement Learning Approach," IEEE Transactions on Network Science and Engineering, vol. 7, no. 1, pp. 66-79, Jan.-Mar. 2020.
      10. M. Sookhak, Helen Tang, Y. He, and F. Richard Yu, ``Security and Privacy of Smart Cities: A Survey, Research Issues and Challenges," IEEE Communications Surveys & Tutorials, vo. 21, no. 2, pp. 1718-1743, Secondquarter 2019.
      11. Y. He, F. Richard Yu, Z. Wei, and V.C.M. Leung, ``Trust Management for Secure Cognitive Radio Vehicular Ad Hoc Networks," Elsevier Ad Hoc Networks, vol. 86, pp.154-165, 2019.
      12. Y. Guo, F. Richard Yu, J. An, K. Yang, Y. He, and V.C.M. Leung, ``Buffer-Aware Streaming in Small-Scale Wireless Networks: A Deep Reinforcement Learning Approach," , IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6891-6902, Jul. 2019.
      13. Y. He, F. Richard Yu, N. Zhao, and H. Yin, ``Secure Social Networks in 5G Systems with Mobile Edge Computing, Caching and Device-to-Device (D2D) Communication," IEEE Wireless Communications, vol. 25, no. 3, pp.103-109, Feb. 2018.
      14. Y. He, N. Zhao, and H. Yin, ``Integrated Networking, Caching, and Computing for Connected Vehicles: A Deep Reinforcement Learning Approach," IEEE Transactions on Vehicular Technology, vol. 67, no.1, pp. 44-55, Jan. 2018.
      15. Y. He, Z. Wei, G. Du, J. Li, N. Zhao, H. Yin, ``Securing Cognitive Radio Vehicular Ad hoc Networks with Fog Computin," Adhoc & Sensor Wireless Networks, vol. 40, no. 1/2, pp. 73-95, 2018.
      16. C. Liang, Y. He, F. Richard Yu, and N. Zhao, "Enhancing Video Rate Adaptation with Mobile Edge Computing and Caching in Software-defined Mobile Networks," IEEE Transactions on Wireless Communications, vol. 17, no. 10, pp. 7013-7026, Oct. 2018.
      17. F. Richard Yu, J. Liu, Y. He, P. Si, and Y. Zhang, ``Virtualization for Distributed Ledger Technology (vDLT)," IEEE Access, vol. 6, pp. 25019-25028, 2018.
      18. Y. He, Z. Zhang, F. Richard Yu, N. Zhao, H. Yin, and V.C.M. Leung, ``Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networks," IEEE Transactions on Vehicular Technology, vol. 66, no. 11, pp. 10433-10445, Nov. 2017.
      19. Y. He, F. Richard Yu, N. Zhao, V.C.M. Leung, and H. Yin, ``Software-defined Networks with Mobile Edge Computing and Caching for Smart Cities: A Big Data Deep Reinforcement Learning Approach," IEEE Communications Magazine, vol. 55, no. 12, pp.31-37, Dec. 2017.
      20. L. Zhu, Y. He, F. Richard Yu, B. Ning, T. Tang, and N. Zhao, ``Communication-Based Train Control System Performance Optimization Using Deep Reinforcement Learning," IEEE Transactions on Vehicular Technology, vol. 66, no. 12, pp. 10705-10717, Dec. 2017.
      21. C. Liang, Y. He, F. Richard Yu, and N. Zhao, ``Enhancing QoE-aware Wireless Edge Caching with Software-defined Wireless Networks," IEEE Transactions on Wireless Communications, vol. 16, no. 10, pp. 6912-6925, Oct. 2017.
      22. C. Wang, Y. He, F. Richard Yu, Q. Chen, and L. Tang, ``Integration of Networking, Caching and Computing in Wireless Systems: A Survey, Some Research Issues and Challenges," IEEE Communications Surveys & Tutorials, vol. 20, no. 1, pp. 7-38, 2017.
      23. J. Guo, B. Song, Y. He, F. Richard Yu, and M. Sookhaku, ``A Survey on Compressed Sensing in Vehicular Infotainment Systems," IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2662-2680, Fourthquarter 2017.
      24. M. Sookhak, F. Richard Yu, Y. He, H. Talebian, N. Zhao, M. K. Khan, and N. Kumar, ``Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing," IEEE Vehicular Technology Magazine, vol. 12, no. 3, pp. 55-64, Sept. 2017.
      25. Y. He, F. R. Yu, N. Zhao, H. Yin, H. Yao and R. C. Qiu, ``Big Data Analytics in Mobile Cellular Networks," IEEE Access, vol. 4, pp. 1985-1996, 2016.
      26. Y. He, H. Yin, and N. Zhao, ``Multiuser-diversity-based interference alignment in cognitive radio networks," AEU-International Journal of Electronics and Communications, vol. 70, no. 5, pp. 617-628, May, 2016.

      Conference Papers

      1. Y. He, Y. Wang, Q. Lin, J. Li, and Victor C.M. Leung, ``A Fast-adaptive Edge Resource Allocation Strategy for Dynamic Vehicular Networks," in Proc. IEEE 29th International Conference on Network Protocols (ICNP), Dallas, TX, USA, Nov. 2021.
      2. Y. He, K. Huang, G. Zhang, J. Li, J. Chen, and Victor C.M. Leung, ``A Blockchain-Enabled Federated Learning System with Edge Computing for Vehicular Networks," in Proc. IEEE Globecom Workshops (GC WKshps), Madrid, Spain, Dec. 2021.
      3. Y. Wang, Y. He, M. Dong, ``Resource Allocation in Vehicular Networks with Multi-UAV Served Edge Computing," in Proc. IEEE 29th International Conference on Network Protocols (ICNP), Dallas, TX, USA, Nov. 2021.
      4. S. Zhuang, Y. He, F. Richard Yu, C. Gao, W. Pan, and Z. Ming, ``When Multi-access Edge Computing Meets Multi-area Intelligent Reflecting Surface: A Multi-agent Reinforcement Learning Approach," in Proc. IEEE/ACM 30th International Symposium on Quality of Service (IWQoS), Oslo, Norway, June 2022.
      5. S. Zhuang, C. Gao, Y. He, F. Richard Yu, Y. Wang, W. Pan, Z. Mingg, ``Qc-DQN: A Novel Constrained Reinforcement Learning Method for Computation Offloading in Multi- access Edge Computing," in Proc. International Joint Conference on Neural Networks (IJCNN ), Padua, Italy, July 2022.
      6. G. Zou, Y. He, F. Richard Yu, L. Chen, W. Pan, and Z. Ming, ``Multi-Constraint Deep Reinforcement Learning for Smooth Action Control," in Proc. 31st International Joint Conference on Artificial Intelligence (IJCAI-22), Vienna, Austria, July 2022.
      7. Y. He, C. Liang, F. Richard Yu, and V.C.M. Leung, ``Integrated Computing, Caching and Communication for Social Networks: A Big Data DRL Approach," in Proc. 2018 IEEE Global Communications Conference (Globecom), Abu Dhabi, UAE, Dec. 2018.
      8. Y. He, F. Richard Yu, and A. Boukerche, ``Deep Reinforcement Learning-Based Resource Management in Software-Defined and Virtualized Vehicular Ad Hoc Networks," in Proc. 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications (DIVANet-17), Miami Beach, FL, Nov. 2017.
      9. Y. He, C. Liang, Z. Zhang, F. Richard Yu, N. Zhao, H. Yin, Y. Zhang, ``Resource Allocation in Software-defined and Information-Centric Vehicular Networks with Mobile Edge Computing," in Proc. IEEE 86th Vehicular Technology Conference (VTC-Fall), Toronto, Canada, Sept. 2017.
      10. C. Liang, Y. He, F. Richard Yu, and N. Zhao, ``Video Rate Adaptation and Traffic Engineering in Mobile Edge Computing and Caching-enabled Wireless Networks," in Proc. IEEE 86th Vehicular Technology Conference (VTC-Fall), Toronto, Canada, Sept. 2017.
      11. C. Liang, Y. He, F. Richard Yu, and N. Zhao, ``Energy-Efficient Resource Allocation in Software-Defined Mobile Networks with Mobile Edge Computing and Caching," in Proc. IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Atlanta, GA, May 2017.
      12. Y. He, C. Liang, F. Richard Yu, N. Zhao, and H. Yin, ``Optimization of Cache-enabled Opportunistic Interference Alignment Wireless Networks: A Big Data Deep Reinforcement Learning Approach," in Proc. IEEE International Conference on Communications (ICC), Paris, France, May 2017.
      13. X. Zhang, F. Richard Yu, Y. He, and N. Zhao, ``Spectrum-Efficient Topology Management of Asymmetric Interference Alignment Networks," in Proc. IEEE/CIC International Conference on Communications in China (ICCC), Shanghai, P.R. China, Oct. 2014.
      14. Y. He, H. Yin, F. Richard Yu, and N. Zhao, ``Performance Improvements of Interference Alignment with Multiuser Diversity in Cognitive Radio Networks," in Proc. IEEE International Conference on Wireless Communications and Signal Processing (WCSP), Hangzhou, China, Nov. 2013.

      Book

      1. F. Richard Yu and Y. He, Deep Reinforcement Learning for Wireless Systems, Springer, 2018.

      Book Chapters

      1. Y. He, Deep reinforcement Learning for Integrated Communication, Caching and Computing, Encyclopedia of Wireless Networks, Springer, 2018.
      2. C. Wang, Y. He, F. Richard Yu, Q. Chen, and L. Tang, Performance Metrics and Enabling Technologies, Integrated Networking, Caching and Computings, Edited by F. Richard Yu, ISBN 978-1-1380-8903-7, CRC Press, 2018.
      3. C. Liang, Y. He, and F. Richard Yu, Edge Caching with Wireless Software-Defined Networking (SDN), Integrated Networking, Caching and Computings, Edited by F. Richard Yu, ISBN 978-1-1380-8903-7, CRC Press, 2018.