The integration of Internet of Vehicles (IoV) and blockchain technology ensures the security of IoV data. As an asynchronous Byzantine fault-tolerant directed acyclic graph (DAG) consensus, Hashgraph consensus effectively addresses the performance bottleneck of a single block-producing node in IoV. However, there are still limitations, such as malicious behavior and node passivity in IoV. The process of Hashgraph consensus relies on the interactions between individual nodes. However, malicious behavior and negative interactions of nodes can reduce the performance and efficiency of consensus. To tackle the issues, this paper proposes a reputation-enhanced Hashgraph consensus. A reputation model is developed to calculate the reputation scores of nodes. The virtual voting weights are dynamically adjusted based on these reputation scores during the consensus process. The proposed consensus mechanism reduces the influence of both the malicious nodes and the passive nodes in the consensus voting process, and strengthens the voting weight of high-reputation nodes. It improves the performance and efficiency of the consensus process. Simulation experiments show that, compared to Hashgraph consensus, the proposed consensus mechanism shows improved throughput performance in IoV scenarios and exhibits strong resistance in scenarios with a majority of malicious nodes.

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A Reputation-Enhanced Hashgraph Consensus Mechanism for Internet of Vehicles

  • Junjie Zhou,
  • Zhihao Hou,
  • Gansen Zhao,
  • Qizhi Zhang

摘要

The integration of Internet of Vehicles (IoV) and blockchain technology ensures the security of IoV data. As an asynchronous Byzantine fault-tolerant directed acyclic graph (DAG) consensus, Hashgraph consensus effectively addresses the performance bottleneck of a single block-producing node in IoV. However, there are still limitations, such as malicious behavior and node passivity in IoV. The process of Hashgraph consensus relies on the interactions between individual nodes. However, malicious behavior and negative interactions of nodes can reduce the performance and efficiency of consensus. To tackle the issues, this paper proposes a reputation-enhanced Hashgraph consensus. A reputation model is developed to calculate the reputation scores of nodes. The virtual voting weights are dynamically adjusted based on these reputation scores during the consensus process. The proposed consensus mechanism reduces the influence of both the malicious nodes and the passive nodes in the consensus voting process, and strengthens the voting weight of high-reputation nodes. It improves the performance and efficiency of the consensus process. Simulation experiments show that, compared to Hashgraph consensus, the proposed consensus mechanism shows improved throughput performance in IoV scenarios and exhibits strong resistance in scenarios with a majority of malicious nodes.