作者
Yuchuan Fu, Fei Richard Yu, Changle Li, Tom H Luan, Yao Zhang
发表日期
2020/2/19
期刊
Ieee wireless communications
卷号
27
期号
2
页码范围
197-203
出版商
IEEE
简介
The accuracy of the ML model is essential for the further development of AI-enabled CAVs. With the increasing complexity of on-board sensor systems, the large amount of raw data available for learning can however cause big communication burdens and data security issues. To alleviate the communication cost yet improve the accuracy of machine learning with preserved data privacy is an important issue to address in CAVs. In this article, we survey the existing literature toward efficient and secured learning in a dynamic wireless environment. In particular, a BCL framework for AI-enabled CAVs is presented. The framework enables distributed CAVs to train ML models locally and upload to blockchain network to overall utilize the "collective intelligence" of CAVs while avoiding large amounts of data transmission. Blockchain is then applied to protect the distributed learned models. We evaluate the performance of …
学术搜索中的文章
Y Fu, FR Yu, C Li, TH Luan, Y Zhang - Ieee wireless communications, 2020