Research The Data Of Throughput Optimization And Auditing Integrity In Cloud Storage

With the advent of the era of big data, cloud data storage technology based on the Software-as-a-service platform has developed rapidly and Cloud storage service with significant storage and computation resource has becoming more and more popular for users to remote store their data in cloud. Big data current mainly around on availability,performance and recoverability. Firstly, some fiber optic network using XSEDE,ESnet and Internet2 provide high-speed network connectivity to their users. However,majority of the users fail to obtain even a fraction of the theoretical speeds promised by these networks due to issues, such as suboptimal TCP tuning, disk performance bottleneck on the sending and/or receiving ends, and server processor limitations. Secondly, by data outsourcing, users can relieve the burden of local data storage and maintenance. However the fact that users no longer have physical possession of the outsourced data challenges the security of the data in the cloud. To auditing the integrity of data. This paper focuses on the study of throughput optimization and integrity verification of the shared data :In order to solve the problem of low efficiency in the use of data sources and data transmission of the traditional data intensive scalable computing systems, big data throughput optimization algorithm is proposed based on full C-order model with parallel flow prediction. Firstly, a method of equivalent parallel flow algorithm is designed to improve the prediction accuracy of the parallel flow and the utilization of the bottle link;Then, according to the partial C-order model and full Second-order model, the full C-order model is constructed and the low sample throughout optimization framework is designed to reduce the computational complexity; The experiments on the data set with different size show that the full C-order model with parallel flow could be more suitable for transmission of big data, and be more efficient.With the development of data service in the cloud, it's very common that people work together as a group. Every member in the group is able to not only access and modify data,but also share the latest version of shared data with the group. However, in the open network,the integrity of the data stored in the cloud are in grave danger of collapsing.Therefore, a scheme for privacy-protected auditing the integrity of shared data on the cloud storage is discussed in this paper. The scheme achieved in the introduction of a third party auditor( TPA) that provide public auditing for share data integrity verification and periodic inspection, and can support dynamic updating shared data, moreover, it can get quick identification of corrupted data.A detailed analysis on solution experiments and mathematical methods show the proposed scheme is secure and efficient.