期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
SBFT:A BFT Consensus Mechanism Based on DQN Algorithm for Industrial Internet of Thing
1
作者 Ningjie Gao Ru Huo +3 位作者 Shuo Wang Jiang Liu Tao Huang Yunjie Liu 《China Communications》 SCIE CSCD 2023年第10期185-199,共15页
With the development and widespread use of blockchain in recent years,many projects have introduced blockchain technology to solve the growing security issues of the Industrial Internet of Things(IIoT).However,due to ... With the development and widespread use of blockchain in recent years,many projects have introduced blockchain technology to solve the growing security issues of the Industrial Internet of Things(IIoT).However,due to the conflict between the operational performance and security of the blockchain system and the compatibility issues with a large number of IIoT devices running together,the mainstream blockchain system cannot be applied to IIoT scenarios.In order to solve these problems,this paper proposes SBFT(Speculative Byzantine Consensus Protocol),a flexible and scalable blockchain consensus mechanism for the Industrial Internet of Things.SBFT has a consensus process based on speculation,improving the throughput and consensus speed of blockchain systems and reducing communication overhead.In order to improve the compatibility and scalability of the blockchain system,we select some nodes to participate in the consensus,and these nodes have better performance in the network.Since multiple properties determine node performance,we abstract the node selection problem as a joint optimization problem and use Dueling Deep Q Learning(DQL)to solve it.Finally,we evaluate the performance of the scheme through simulation,and the simulation results prove the superiority of our scheme. 展开更多
关键词 Industrial Internet of Things Byzantine fault tolerance speculative consensus mechanism Markov decision process deep reinforcement learning
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部