Scholarlink

<p>This paper suggests a better consensus mechanism method for Delegated Proof of Stake (DPoS) in UAV-assisted mobile edge computing (MEC) for Improved Delegated Proof of Stake (I-DPoS) to solve the problems such as the ease of selecting malicious nodes as consensus nodes, the delayed handling of malicious nodes, and the tendency for certain nodes to be selected as consensus nodes without aggressive voting. Firstly, the reputation value model is proposed to calculate each node’s globally unique reputation value <i>Trust</i> in the current election cycle <i>T</i>. Secondly, in the phase of proxy nodes selection, a new evaluation criterion is constructed for proxy node selection. Then, the reputation value of the node is rewarded or punished according to the node's behavior, both of the block-out node and the voting node, the reputation reward is given for successfully generating blocks, and the reputation punishment is given for malicious behavior. Finally, the experimental results show that compared to the Traditional Delegated Proof of Stake (TDPoS) and Anomaly Detection and Reward-Punishment based DPoS (ADRP) algorithms, the I-DPOS algorithm has seen a significant decrease in the proportion of proxy nodes that are maliciously elected, and at a total number of nodes of 36, the network throughput is improved by 17 transactions per second and 8 transactions per second respectively, and the average latency of the outgoing block is reduced by 3.41&#xa0;s and 2.32&#xa0;s respectively.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimization of DPoS consensus mechanism based on reputation value in UAV-assisted MEC

  • 期刊论文

  • 发表日期：

    2025年9月24日

查看全文
  • Sihan Zeng,
  • Haibo Zeng,
  • Peng Zhang,
  • Yaojuan Wu,
  • Kaijun Yang,
  • Chunguang Yang,
  • Wu Zhu,
  • Chunlin Li,
  • Qingren Jia

摘要

This paper suggests a better consensus mechanism method for Delegated Proof of Stake (DPoS) in UAV-assisted mobile edge computing (MEC) for Improved Delegated Proof of Stake (I-DPoS) to solve the problems such as the ease of selecting malicious nodes as consensus nodes, the delayed handling of malicious nodes, and the tendency for certain nodes to be selected as consensus nodes without aggressive voting. Firstly, the reputation value model is proposed to calculate each node’s globally unique reputation value Trust in the current election cycle T. Secondly, in the phase of proxy nodes selection, a new evaluation criterion is constructed for proxy node selection. Then, the reputation value of the node is rewarded or punished according to the node's behavior, both of the block-out node and the voting node, the reputation reward is given for successfully generating blocks, and the reputation punishment is given for malicious behavior. Finally, the experimental results show that compared to the Traditional Delegated Proof of Stake (TDPoS) and Anomaly Detection and Reward-Punishment based DPoS (ADRP) algorithms, the I-DPOS algorithm has seen a significant decrease in the proportion of proxy nodes that are maliciously elected, and at a total number of nodes of 36, the network throughput is improved by 17 transactions per second and 8 transactions per second respectively, and the average latency of the outgoing block is reduced by 3.41 s and 2.32 s respectively.