Research On Data Causal Consistency Model For Cloud-edge Collaboration And Blockchain

Distributed storage systems provide users with highly available data storage and computing services by building multiple replicas,and the key to high availability services is to ensure the consistency of data states between replicas.In the research of data consistency,causal consistency has been widely studied due to its performance advantages.With the rapid expansion of the Internet scale,traditional causal consistency models cannot meet the highperformance requirements of the Internet,so it is particularly important to study how to improve the performance of causal consistency models.In addition,current causal consistency models are mostly studied based on ideal environments,and there are few studies on security risks such as untrusted data transmission channels and malicious nodes tampering with user data in actual distributed environments.Therefore,while improving the performance of causal consistency models,security constraints must also be placed on the system.In view of the above problems,this paper mainly does the following work:(1)Addressing the problems of large data synchronization,high metadata storage overhead and high user request response delay in the current distributed storage causal consistency scheme,a causal consistency scheme based on partial replication and cloud-edge collaboration is proposed.The scheme designs a client-edge-cloud storage model based on partial geographic replication strategy on the basis of the cloud-edge collaboration architecture,and timely processes and responds to user requests at the edge node,reducing the high response delay of user requests.The adjacency relationship between edge nodes and partitions is described by a matrix,and a global stability mechanism and metadata processing service are established to ensure the causal consistency of data synchronization between nodes,reducing the overhead of system data synchronization and metadata processing.(2)To address security risks such as sensitive data leakage and illegal data tampering by Byzantine nodes in distributed network environments,a causal consistency scheme based on blockchain network and trusted validation is proposed.The edge-cloud storage blockchain network is constructed based on the cloud-edge collaboration architecture,and security constraints are placed on the consistency of data reading,writing,and synchronization through trusted signatures and blockchain security consensus.The FBFT consensus algorithm is used to achieve data synchronization,reducing the overhead of traditional broadcast-style data synchronization.Smart contracts and reputation management models are introduced to prevent malicious nodes from being elected as leaders to carry out illegal behavior and improve the overall security of the system.Through simulation experiments,it is proved that the proposed scheme can achieve efficient data synchronization and reliable security constraints with small performance overhead.