近年来部分代表性论文:
1
Xi Lin, Jun Wu, Jianhua
Li, Chao Sang, Shiyan Hu and M. Jamal Deen, Heterogeneous
Differential-Private Federated Learning: Trading Privacy for Utility
Truthfully, in IEEE Transactions on Dependable and Secure Computing (TDSC), doi: 10.1109/TDSC.2023.3241057. (CCF-A, SCI Q1, IF: 7.3)
2
Xi Lin, Jun Wu, Jianhua
Li, Wu Yang, Mohsen
Guizani,
Stochastic Digital-Twin Service Demand with Edge Response: An Incentive-Based Congestion Control Approach, in
IEEE Transactions on Mobile Computing (TMC), vol. 22, no. 4, pp.
2402-2416, 1 April 2023. (CCF-A,
SCI Q1, IF: 7.9)
3
Xi Lin, Jun Wu, Jianhua Li, Xi Zheng, Gaolei Li,
Friend-as-Learner: Socially-Driven Trustworthy and Efficient Wireless Federated
Edge Learning, in IEEE Transactions on Mobile Computing (TMC), vol. 22,
no. 1, pp. 269-283, 1 Jan. 2023. (CCF-A, SCI Q1, IF: 7.9)
4 Xi Lin, Jun Wu, Ali Kashif
Bashir, Wu Yang, Aman Singh, Ahmad Ali
AlZubi, FairHealth: Long-Term Proportional
Fairness-Driven 5G Edge Healthcare in Internet of Medical Things, in IEEE Transactions on Industrial Informatics,
vol. 18, no. 12, pp. 8905-8915, Dec. 2022. (SCI Q1 Top, IF: 12.3)
5
Xi Lin, Jun
Wu, Shahid Mumtaz, Mohsen Guizani,
et al, Blockchain-Based On-Demand
Computing Resource Trading in IoV-Assisted Smart City, in IEEE Transactions on Emerging Topics in
Computing (TETC), vol. 9, no. 3, pp. 1373-1385, 1 July-Sept, 2021. (ESI
Highly Cited Paper (1%), ESI Hot Paper (0.1%), SCI Q1
Top, IF: 5.9)
6
Xi Lin, Jianhua Li, Jun Wu, et
al, Making Knowledge Tradable in Edge-AI Enabled IoT: A Consortium Blockchain-Based Efficient and Incentive Approach,
in IEEE Transactions on Industrial Informatics (TII), vol. 15, no. 12,
pp. 6367-6378, Dec. 2019. (ESI Highly Cited Paper (1%), SCI Q1 Top, IF: 12.3)
7
Xi Lin, Jun Wu, Ali Kashif Bashir, Jianhua
Li, Wu Yang, Jalil
Piran, Blockchain-Based Incentive Energy-Knowledge Trading
in IoT: Joint Power Transfer
and AI Design, in IEEE Internet of Things Journal (IoT-J), vol. 9, no. 16, pp. 14685-14698, 15 Aug.15, 2022. (ESI Highly Cited Paper (1%), SCI Q1 Top, IF: 10.6)