Cloud Disaster Tolerance And Conformance Storage Strategy

In recent years,cloud storage has become a widely accepted model of data storage.With the continuous development of the application of cloud storage in various fields,the security problem of cloud storage has attracted people's special attention.The cloud platform can support the reliability of the data through data backup.The cloud storage system backs up multiple copies across geographical areas to different data centers.When data stored in the original data center is damaged or lost,copies of other data centers can restore the data in the original data center.Using the data backup method,the user selects a copy for access,which can reduce the access pressure of a single node and improve the availability of data.However,the introduction of data disaster tolerance backup also brings about many problems,such as bandwidth overhead,data consistency,load balancing and so on.This dissertation presents a hierarchical disaster recovery storage strategy for cloud service providers to ensure the reliability of data and different QoS(Quality of Service)requirements of user tasks.The storage resources of cloud service providers are graded according to service level to build a cloud computing fault tolerance model to meet different QoS requirements.On this basis,the storage resources are classified and managed according to service levels to improve the cloud service provider resource utilization.For the consistency problem brought by the copy,by constructing a high-performance buffer,we use parameter probability distribution strategy to buffer some of the strong consistency data to improve the availability of strong consistency data.The correctness of the above strategies are analyzed theoretically,and the effectiveness of the strategies are verified by simulation.