Yun Wu
Editorial Notes
EXPRESSION OF CONCERN: ACM is issuing a formal Expression of Concern for all papers published in the TOSN Special Issue on Green Communications and Sensor Networks with Machine Intelligence for Smart Cities while a thorough investigation takes place with regards to the integrity of the peer review process. ACM strongly suggests that papers in this special issue not be cited in the literature until ACM's investigation has concluded and final decisions have been made regarding the integrity of the peer review process.
Abstract
Internet of Vehicles(IoV) enables vehicles to generate and share messages to improve transportation safety and efficiency, especially in a smart city scenario where modern communication technology is utilized. The current IoV, however, faces three main issues: (1) existing frameworks fail to build a complete data management system, (2) received messages in an untrusted environment are challenging to assess for credibility, and (3) the centralized ways to store data are causing severe security and efficiency problems. Blockchain-enabled IoV (BIoV) provides an opportunity for addressing these issues. This paper proposes a trusted paradigm of data management based on a vehicle–road–cloud architecture. A few-shot learning model, Wasserstein Generative Adversarial Network (WGAN) with Synthetic Minority Oversampling Technique (SMOTE) sampling is designed to evaluate whether the uploading message is malicious. This paper also proposes the novel group-weighted-decay Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, an improved version of PBFT to store data, and provides a comprehensive review of its viability and data management procedures. By employing the joint gwd-PBFT and Proof of Trust (PoT) consensus, the method mitigates the issue of excessive incentives. According to simulation results, the system's overall efficiency can be increased while retaining security and availability.
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