Author

Haixia Zhang

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2026

Delay-Driven Vehicle Scheduling and Resource Optimization for Multi-Task Federated Learning in Heterogeneous Vehicular Networks

Federated learning (FL) has become a promising paradigm for privacy-preserving and communication-efficient model training in vehicular networks. With the continuous expansion of vehicular networks, multiple FL tasks are often initiated concurrently by moving vehicles, which poses substantial challenges to the conventio...

Xiao-Na Jiang, Jie Tian, Tian-Tian Li et al. · IEEE Transactions on Cogniti... · 0 citations

2026

Mobility-Aware Vehicle Selection and Bandwidth Allocation for Federated Learning in Vehicular Networks: An HPPO Approach

Federated learning (FL) has emerged as a promising paradigm for enabling distributed model training in vehicular networks while keeping raw data local. However, the dynamic mobility of vehicles and the limited spectrum resources create critical challenges for efficient FL execution. In particular, due to the high mobil...

Zichao Zhao, Haixia Zhang, Wenjie Liu et al. · IEEE Transactions on Cogniti... · 0 citations