The Research And Application Of Cloud Computing Data Storage Model

With the extensive application of information technology and the rapiddevelopment of cloud computing as a new business computing model increasingattention has been widespread concern. However, the lack of reliability cloudcomputing data storage security. In view of this, this article mainly researches andanalyzes the user data storage model of cloud computing, through learning the relatedmachine and building the model of CP-ABE algorithm, improves the model ofMap/Reduce algorithm, and promotes access speed.In this paper, on the basis of previous studies, mainly engaged in the work of thefollowing aspects:First, the traditional symmetric encryption algorithms exist, such as their ownsafety is not high, the encryption and decryption using the same key the keydissemination of security problems inherent in, and the large amount of computationof asymmetric encryption system for large data processing drawbacks, study theproperties of the ciphertext encryption algorithm CP-ABE algorithm uses a monotoneaccess control tree, collection of the relevant properties of the server-side internalnodes and leaf junction point of access control tree, so as to ensure that the cloudcomputing system is safe and reliable, and the algorithm compared to traditionalsymmetric and asymmetric encryption algorithm with a key server for centralizedmanagement. Access control model based on the CP-ABE algorithm can control theinitiative by the encryption side, only to meet the requirements of the ciphertext userscan decrypt permission. The mechanism to reduce the complexity of the rightsmanagement and access control information storage space;Secondly, the Map/Reduce model does not consider a large number ofheterogeneous nodes in the cluster computing performance in the alloca tion of theinput file, the increase in the amount of network data transfer when running the maptask, the subject for the problem in a cloud computing environment improvedMap/Reduce model, to reduce fuzzy granularity in the classification process. Cloudcomputing environment different nodes in the cluster computing performance anddifferent design improved index classification storage models and algorithms in theMap/Reduce results inverted index table and2times Map/Reduce the calculation ofthe index word weight measure of segment, so that the index data is no longer a simple inverted index table after two sub-categories, but to the weight thresholdCategory reverse index table, thereby increasing data storage capacity and computingspeed;Finally, the combination of the school experimental conditions situation, buildhadoop platform to simulate large heterogeneous cloud environments, and verify theeffectiveness and efficiency of the proposed algorithm and Map/Reduce model.