The explosive growth of data in the network has brought huge burdens and challenges to traditional centralized cloud computing data processing. To solve this problem, edge computing technology came into being. Because the edge is closer to the user, processing part of the data at the edge can also bring a faster response to the user and improve their experience. However, the existing edge computing platforms have problems such as data storage security and multiparty data mutual trust. Blockchain technology has become an important means to solve the above data storage and sharing problems due to its excellent characteristics. The core of blockchain technology is consensus, and its speed and security will directly affect the efficiency and stability of the blockchain system. Therefore, this study uses the consensus mechanism as an entry point to reduce the resource consumption of the edge computing blockchain system and improve its security. In order to reduce the resource consumption of traditional consensus algorithms, improve their adaptability in the edge computing environment, and solve the security problem caused by the concentration of node rights, a prestige-based edge computing blockchain security consensus model (ECBCM) is proposed. ECBCM is a general model based on prestige rewards and penalties. It also introduces a node replacement mechanism to ensure the fault tolerance of the consensus process. According to the results of multiple sets of performance comparison experiments and security verification experiments after embedding the existing consensus algorithm, the validity of the consensus model is confirmed.

中文翻译：

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ECBCM：一种基于信誉的边缘计算区块链安全共识模型

网络中数据的爆炸式增长给传统的中心化云计算数据处理带来了巨大的负担和挑战。为了解决这个问题，边缘计算技术应运而生。因为边缘离用户更近，在边缘处理部分数据也可以给用户带来更快的响应，提升他们的体验。然而，现有的边缘计算平台存在数据存储安全、多方数据互信等问题。区块链技术以其优异的特性成为解决上述数据存储和共享问题的重要手段。区块链技术的核心是共识，其速度和安全性将直接影响区块链系统的效率和稳定性。所以，本研究以共识机制为切入点，降低边缘计算区块链系统的资源消耗，提高其安全性。为了减少传统共识算法的资源消耗，提高其在边缘计算环境中的适应性，解决节点权限集中带来的安全问题，提出了一种基于信誉的边缘计算区块链安全共识模型（ECBCM）。ECBCM 是一种基于声望奖励和惩罚的通用模型。它还引入了节点替换机制来保证共识过程的容错性。根据嵌入现有共识算法后的多组性能对比实验和安全验证实验的结果，验证了共识模型的有效性。