Publications

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Author Title Type [ Year(Desc)]
2016
M. Li, He, P. , and Zhao, L. , “Dynamic Elastic Load Scheduling Achieving Load Balancing for Smart Grid”, in IEEE/CIC International Conference on Communications in China (ICCC), Chengdu, China, 2016, pp. 1-6.
L. Ferdouse, Li, M. , Guan, L. , and Anpalagan, A. , “Bayesian Workload Scheduling in Multimedia Cloud Networks”, in IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), Toronto, Canada, 2016, pp. 1-6.
2017
M. Baljon, Li, M. , Liang, H. , and Zhao, L. , “SMDP-Based Resource Allocation for Wireless Networks with Energy Harvesting Constraints”, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017, pp. 1-5.
J. Gao, Li, M. , He, P. , and Zhao, L. , “Incentive for Distributed Optimization in Multi-User Network: A Study of Two Scenarios”, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017.
M. Li and Zhao, L. , “A Decentralized Load Balancing Approach for Neighbouring Charging Stationsvia EV Fleets”, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017, pp. 1-5.
M. Li, He, P. , and Zhao, L. , “Load Balancing Applying Water-Filling Approach in Smart Grid Systems”, IEEE Internet of Things Journal, vol. 4, no. 1, pp. 247-257, 2017.
M. Li, Zhao, L. , and Liang, H. , “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, 2017.
2018
P. He, Li, M. , Zhao, L. , Venkatesh, B. , and Li, H. , “Water-Filling Exact Solutions for Load Balancing of Smart Power Grid Systems”, IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 1397-1407, 2018.
J. Gao, Li, M. , Zhao, L. , and Shen, X. , “Contention Intensity Based Distributed Coordination for V2V Safety Message Broadcast”, IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 12288-12301, 2018.
2019
M. Li, Gao, J. , Zhao, L. , and Shen, X. , “Task Time Allocation and Reward Scheme for PEV Charging Station Advertising”, in IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-6.
M. Chen, Li, M. , Wang, M. , Ma, J. , and Shen, X. , “Compensation of Charging Station Overload via On-road Mobile Energy Storage Scheduling”, in IEEE Global Communications Conference (GLOBECOM), Hawaii, USA, 2019, pp. 1-6.
N. Chen, Ma, J. , Li, M. , Wang, M. , and Shen, X. , “Energy Management Framework for Mobile Vehicular Electric Storage”, IEEE Network, vol. 33, no. 6, pp. 148-155, 2019.
2020
M. Li, Gao, J. , Zhang, N. , Zhao, L. , and Shen, X. , “Collaborative Computing in Vehicular Networks: A Deep Reinforcement Learning Approach”, in IEEE International Conference on Communications (ICC), virtual/Dublin, Ireland, 2020, pp. 1-6.
X. Shen et al., “AI-Assisted Network-SlicingBased Next-Generation Wireless Networks”, IEEE Open Journal of Vehicular Technology, vol. 1, pp. 45-66, 2020.
M. Li, Gao, J. , Chen, N. , Zhao, L. , and Shen, X. , “Decentralized PEV Power Allocation with Power Distribution and Transportation Constraints”, IEEE Journal on Selected Areas in Communications, vol. 38, no. 1, pp. 229-243, 2020.
M. Li, Cheng, N. , Gao, J. , Wang, Y. , Zhao, L. , and Shen, X. , “Energy-Efficient UAV-Assisted MobileEdge Computing: Resource Allocation and Trajectory Optimization”, IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 3424-3438, 2020.
F. Wang, Gao, J. , Li, M. , and Zhao, L. , “Autonomous PEV Charging Scheduling Using Dyna-Q Reinforcement Learning”, IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 12609-12620, 2020.
M. Li, Gao, J. , Zhao, L. , and Shen, X. , “Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks”, IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 4, pp. 1122- 1135, 2020.
2021
N. Chen, Li, M. , Wang, M. , Su, Z. , Li, J. , and Shen, X. , “A Dynamic Pricing Based Scheduling Scheme for Electric Vehicles as Mobile Energy Storages”, in IEEE International Conference on Communications (ICC), 2021.
H. Liang et al., “Reinforcement Learning Enabled Dynamic Resource Allocation in the Internet of Vehicles”, IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4957-4967, 2021.

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