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July 10, 2026International Journal of Innovative Computing and Applications0 citations

Hierarchical Asynchronous Federated Learning Method for Blockchain-enabled Vehicle Networking Integrating Spatio-temporal Trajectory Characteristics

LZLi Ting ZhangYWYunfei WangHZHou Fu Zhang

Key Points

  • The research aims to develop a hierarchical asynchronous federated learning method to optimize vehicle networking using spatio-temporal trajectory data.
  • Developed a hierarchical federated learning framework for vehicle networking.
  • Utilized blockchain technology to enhance data security and collaboration.
  • Implemented spatio-temporal trajectory analysis for data integration.
  • Achieved improved data processing speed in vehicle networking systems.
  • Enhanced collaboration efficiency among vehicles using hierarchical learning.
  • Provided insights into the integration of blockchain for secure vehicle communications.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a508bde6eeac72a437a0418https://doi.org/10.1504/ijica.2027.10079755
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