A Secure Cloudlet-Based Charging Station Recommendation for Electric Vehicles Empowered by Federated Learning

【Author】 Teimoori, Zeinab; Yassine, Abdulsalam; Hossain, M. Shamim

【Source】IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

【影响因子】11.648

【Abstract】The fast-growing electric vehicles (EVs) industry requires a well-designed recommendation system to locate charging stations while ensuring private data protection. This article proposes a secure cloudlet-based recommendation system for EVs. Unlike conventional methods where training a recommender model involves direct data sharing between data holders, our model utilizes a secure vertical federated learning technique, in which EVs data do not leave the platforms. To improve the efficiency of the model and to alleviate the communication-related concerns in our recommender model, cloudlet-based data aggregator(s) are used as a replacement for the existing centralized architectures. To enhance the security of our system, blockchain technology is incorporated to generate a trusted network of cloudlets that are responsible for transmitting the locally computed training parameters. The simulation results achieved from our proposed recommendation system show that the distribution of EVs over a designated area with charging stations is more optimal, and the proposed decentralized recommender with 10 cloudlets is 5.2 s quicker than a conventional centralized model.

【Keywords】Blockchains; Cloud computing; Data models; Collaborative work; Charging stations; Training; Real-time systems; Blockchain; charging station recommendation; cloudlet; electric vehicles (EVs); vertical federated learning (VFL)

【发表时间】2022 SEP

【收录时间】2022-06-26

【文献类型】实证性文章

【主题类别】

区块链应用-实体经济-能源领域