An Incentive Mechanism Based on AoU, Data Quality, and Data Quantity for Federated Learning. - Zhaohua Zheng; Yiming Hong; Keqiu Li; Qiquan Chen (CSCWD, 2024)

FedAHP: A Heterogeneous Client Selection Method for Federated Learning Based on the Analytic Hierarchy Process in Mobile Edge. - Zhaohua Zheng; Zizheng Wang; Xinyu Tong; Keqiu Li; Qiquan Chen (CSCWD, 2024)

An Uncertainty-Aware Multi-Dimensional Auction Mechanism Based on Age of Update for Federated Learning. - Huang Yue; Zhaohua Zheng; Yiming Hong; Yunwei Song; Qiquan Chen (CSCWD, 2025)

A Contextual Client Selection Method for Volatile Federated Learning. - Zizheng Wang; Zhaohua Zheng; Qiquan Chen (ICCCN, 2025)

A multi-dimensional incentive mechanism based on age of update in hierarchical federated learning. - Zhaohua Zheng; Yiming Hong; Xin Xie 001; Keqiu Li; Qiquan Chen (Softw. Pract. Exp., 2025)