Publications

Books

• M. Li, J. Gao, X. Shen and L. Zhao, Intelligent Computing and Communication for the Internet of Vehicles. eBook ISBN 978-3-031-22860-5, Print ISBN 978-3-031-22859-9, Springer, 2023.
• J. Gao, M. Li, and W. Zhuang, Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions. eBook ISBN 978-3-030-88743-8, Print ISBN 978-3-030-88742-1, Springer, 2021.
  

Journal Paper

• M. Li, J. Gao, C. Zhou, L. Zhao, and X. Shen, “Digital Twin-Empowered Resource Allocation for On-Demand Collaborative Sensing,” IEEE Internet of Things Journal, accepted, 2024.
• M. Li, J. Gao, C. Zhou, X. Shen, and W. Zhuang, “User Dynamics-Aware Edge Caching and Computing for Mobile Virtual Reality,” IEEE Journal of Selected Topics in Signal Processing, vol. 17, no. 5, pp. 1131-1146, Sept. 2023.
• M. Li, J. Gao, L. Zhao, and X. Shen, “Adaptive Computing Scheduling for Edge-assisted Autonomous Driving,” IEEE Transactions on Vehicular Technology, vol. 70, no. 6, pp. 5318-5331, June 2021.
• M. Li, J. Gao, C. Zhou, X. Shen, and W. Zhuang “Slicing-Based Artificial Intelligence Service Provisioning on the Network Edge: Balancing AI Service Performance and Resource Consumption of Data Management,” IEEE Vehicular Technology Magazine, vol. 16, no. 4, pp. 16-26, Dec. 2021.
• M. Li, J. Gao, L. Zhao, and X. Shen, “Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks,” IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 4, pp. 1122-1135, Dec. 2020.
• M. Li, N. Cheng, J. Gao, Y. Wang, L. Zhao and X. Shen, “Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization,” IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 3424-3438, Mar. 2020.
• M. Li, J. Gao, N. Chen, L. Zhao, and X. Shen, “Decentralized PEV Power Allocation with Power Distribution and Transportation Constraints,” IEEE Journal on Selected Areas in Communications, vol. 38, no.1, pp. 229-243, Jan. 2020.
• M. Li, L. Zhao and H. Liang, “An SMDP-Based Prioritized Channel Allocation Scheme in Cognitive Enabled Vehicular Ad Hoc Networks,” IEEE Transactions on Vehicular Technology, vol. 66, no. 9, pp. 7925-7933, Sept. 2017.
• M. Li, P. He and L. Zhao, “Dynamic Load Balancing Applying Water-Filling Approach in Smart Grid Systems,” IEEE Internet of Things Journal, vol. 4, no. 1, pp. 247-257, Feb. 2017.
• W. Jiang, B. Ai, M. Li, W. Wen, Y. Pei and X. Shen, “Aerial IRSs Assisted Energy-Efficient Task Offloading and Computing,” IEEE Internet of Things Journal, vol. 11, no. 11, pp. 20178-20193, June 2024.
• C. Zhou, J. Gao, M. Li, N. Cheng, X. Shen, W. Zhuang, “Digital Twin-based 3D Map Management for Edge-assisted Device Pose Tracking in Mobile AR,” IEEE Internet of Things Journal, vol. 11, no. 10, pp. 17812-17826, May 2024.
• S. Hu, J. Gao, M. Li, C. Zhou, X. Shen, “Adaptive Device-Edge Collaboration on DNN Inference in AIoT: A Digital Twin-Assisted Approach,” IEEE Internet of Things Journal, vol. 11, no. 7, pp. 12893-12908, April 2024.
• X. Huang, W. Wu, S. Hu, M. Li, C. Zhou, X. Shen, “Digital Twin Based User-Centric Resource Management for Multicast Short Video Streaming,” IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 1, pp. 50-65, Jan. 2024.
• W. Wang, N. Cheng, T. Yang, M. Li, C. Zhou, C. Li, F. Chen, “A Novel Value of Information-Based Resource Scheduling Method for CAVs,” IEEE Transactions on Vehicular Technology, accepted, Jan. 2024.
• Z. Zheng, Z. Li, C. Huang, S. Long, M. Li, X. Shen, “Data Poisoning Attacks and Defenses to LDP-based Privacy-Preserving Crowdsensing,” IEEE Transactions on Dependable and Secure Computing, accepted, Jan. 2024.
• W. Jiang, B. Ai, C. Shen, M. Li and X. Shen, “Age-of-Information Minimization for UAV-enabled Multi-view Sensing and Communication,” IEEE Transactions on Vehicular Technology, vol. 73, no. 1, pp. 1100-1114, Jan. 2024.
• C. Zhou, J. Gao, M. Li, X. Shen, W. Zhuang, X. Li, W. Shi, “AI-Assisted Slicing-Based Network Planning for Two-Tier Radio Access,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 6, pp. 1691-1706, Dec. 2023.
• K. Qu, W. Zhuang, W. Wu, M. Li, X. Shen, and X. Li, “Stochastic Cumulative DNN Inference with RL-Aided Adaptive IoT Device-Edge Collaboration,” IEEE Internet of Things Journal, vol. 10, no. 20, pp. 18000-18015, Oct. 2023.
• W. Jiang, B. Ai, M. Li, W. Wen and X. Shen, “Average Age of Information Minimization in Aerial IRS-Assisted Data Delivery,” IEEE Internet of Things Journal, vol. 10, no. 17, pp. 15133-15146, Sept. 2023.
• W. Wu, M. Li, K. Qu, C. Zhou, X. Shen, W. Zhuang, X. Li and W. Shi, “Split Learning over Wireless Networks: Parallel Design and Resource Management,” IEEE Journal on Selected Areas in Communications, vol. 10, no. 17, pp. 15133-15146, Sept. 2023.
• X. Shen, J. Gao, M. Li, C. Zhou, M. He, and W. Zhuang, “Towards Immersive Communications in 6G,” Frontier in Computer Science, vol. 4, pp. 1-31, 2023.
• C. Zhou, J. Gao, M. Li, X. Shen, and W. Zhuang, “Digital Twin-Empowered Network Planning for Multi-Tier Computing,” Journal of Communications and Information Networks, vol. 7, no. 3, pp. 221-238, Sept. 2022.
• X. Shen, J. Gao, W. Wu, M. Li, C. Zhou, and W. Zhuang “Holistic Network Virtualization and Pervasive Network Intelligence for 6G,” IEEE Communications Surveys and Tutorials, vol. 24, no. 1, pp. 1-30, Firstquarter 2022.
• W. Wu, C. Zhou, M. Li, H. Wu, H. Zhou, N. Zhang, X. Shen, and W. Zhuang “AI-Native Network Slicing for 6G Networks,” IEEE Wireless Communication, vol. 29, no. 1, pp. 96-103, February 2022.
• W. Wu, N. Chen, C. Zhou, M. Li, X. Shen, W. Zhuang, X. Li, “Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 7, pp. 2076-2089, July 2021.
• J. Gao, W. Zhuang, M. Li, X. Shen and X. Li, “MAC for Machine Type Communications in Industrial IoT – Part I: Protocol Design and Analysis,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9945-9957, June 2021.
• J. Gao, W. Zhuang, M. Li, X. Shen and X. Li, “MAC for Machine Type Communications in Industrial IoT – Part II: Scheduling and Numerical Results,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9958-9969, June 2021.
• H. Liang, X. Zhang, X. Hong, Z. Zhang, M. Li, G. Hu, and F. Hou, “Reinforcement Learning Enabled Dynamic Resource Allocation in the Internet of Vehicles,” IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4957-4967, July 2021.
• F. Wang, J. Gao, M. Li and L. Zhao, “Autonomous PEV Charging Scheduling Using Dyna-Q Reinforcement Learning,” IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 12609-12620, Nov. 2020.
• X. Shen, J. Gao, W. Wu, K. Lyu, M. Li, W. Zhuang, X. Li, J. Rao, “AI-Assisted Network-Slicing Based Next-Generation Wireless Networks,” IEEE Open Journal of Vehicular Technology, vol. 1, pp. 45-66, Jan. 2020.
• N. Chen, J. Ma, M. Li, M. Wang and X. Shen, “Energy Management Framework for Mobile Vehicular Electric Storage,” IEEE Network, vol. 33, no. 6, pp. 148-155, Nov.-Dec. 2019.
• J. Gao, M. Li, L. Zhao and X. Shen,”Contention Intensity Based Distributed Coordination for V2V Safety Message Broadcast,” IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 12288-12301, Dec. 2018.
• P. He, M. Li, L. Zhao, B. Venkatesh and H. Li, “Water-Filling Exact Solutions for Load Balancing of Smart Power Grid Systems,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 1397-1407, Mar. 2018.

Conference Paper

• M. Li, J. Gao, C. Zhou, L. Zhao, and X. Shen, “On-Demand Collaborative Sensing with Digital Twin-Driven Resource Allocation,” IEEE VTC 2024-Fall, accepted, 2024.
• M. Li, J. Gao, C. Zhou, X. Shen, and W. Zhuang, “Adaptive Mobile VR Content Delivery for Industrial 5.0,” The 1st ACM MobiCom Workshop on Digital Twin \& Edge AI for IIoT, Sydney, Australia, October 17-21, 2022.
• M. Li, J. Gao, C. Zhou, X. Shen, and W. Zhuang, “Digital Twin-Driven Computing Resource Management for Vehicular Networks,” IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 4-8, 2022.
• M. Li, J. Gao, N. Zhang, L. Zhao and X. Shen, “Collaborative Computing in Vehicular Networks: A Deep Reinforcement Learning Approach,” IEEE International Conference on Communications (ICC), virtual/Dublin, Ireland, June 2020.
• M. Li, J. Gao, L. Zhao and X. Shen, “Task Time Allocation and Reward Scheme for PEV Charging Station Advertising,” IEEE International Conference on Communications (ICC), Shanghai, China, June 2019.
• M. Li and L. Zhao, “A Decentralized Load Balancing Approach for Neighbouring Charging Stations via EV Fleets,” IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, Sept. 2017.
• M. Li, P. He and L. Zhao, “Dynamic Elastic Load Scheduling Achieving Load Balancing for Smart Grid,” IEEE/CIC International Conference on Communications in China (ICCC), Chengdu, China, July 2016.
• S. Hu, J. Gao, X. Huang, M. Li, K. Qu, C. Zhou, and X. Shen, “Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication”, IEEE International Conference on Communications (ICC), Denver, CO, USA, June 9-13, 2024.
• C. Zhou, J. Gao, M. Li, N. Cheng, X. Shen, W. Zhuang, “Digital Twin-Based 3D Map Management for Edge-Assisted Mobile Augmented Reality,” 2023 IEEE/CIC International Conference on Communications in China (ICCC)}, Dalian, Canada, Sept. 2023.
• T. Zheng, Y. Liu, G. Sun, M. Li, C. Zhou, X. Shen, “Energy Efficient UAV-Assisted Communications via Collaborative Beamforming,” 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)}, Toronto, Canada, Sept. 2023.
• X. Huang, M. Li, W. Wu, C. Zhou, X. Shen, “Digital Twin-Assisted Collaborative Transcoding for Better User Satisfaction in Live Streaming,” IEEE International Conference on Communications (ICC)}, Rome, Italy, 28 May - 01 June, 2023.
• Y. Pei, M. Li, H. Wu, C. Zhou, S. Hu, Q. Ye, and X. Shen, “Joint Caching and Computing Resource Reservation for Edge-Assisted Location-Aware Augmented Reality,” IEEE International Conference on Communications (ICC)}, Rome, Italy, 28 May - 01 June, 2023.
• X. Huang, C. Zhou, W. Wu, M. Li, H. Wu, and X. Shen, “Personalized QoE Enhancement for Adaptive Video Streaming: A Digital Twin-Assisted Scheme,” IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 4-8, 2022.
• S. Hu, M. Li, J. Gao, C. Zhou, and X. Shen, “Digital Twin-Assisted Adaptive DNN Inference in Industrial Internet of Things,” IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 4-8, 2022.
• N. Chen, M. Li, M. Wang, Z. Su, J. Li, and X. Shen, “A Dynamic Pricing Based Scheduling Scheme for Electric Vehicles as Mobile Energy Storages,” IEEE International Conference on Communications (ICC), virtual/Montreal, Canada, June 2021.
• N. Chen, M. Li, M. Wang, J. Ma, and X. Shen, “Compensation of Charging Station Overload via On-road Mobile Energy Storage Scheduling,” IEEE Global Communications Conference (GLOBECOM), Hawaii, USA, Dec. 2019.
• J. Gao, M. Li, P. He, and L. Zhao, “Incentive for Distributed Optimization in Multi-User Network: A Study of Two Scenarios,” IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, Sept. 2017.
• M. Baljon, M. Li, H. Liang, and L. Zhao, “SMDP-Based Resource Allocation for Wireless Networks with Energy Harvesting Constraints,” IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, Sept. 2017.
• L. Ferdouse, M. Li, L. Guan and A. Anpalagan, “Bayesian Workload Scheduling in Multimedia Cloud Networks,” IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), Toronto, Canada, Oct. 2016.