Simulation of Network Data Deduplication Using Improved Autoregressive Models in Cloud Environment
In the process of network data deduplication in cloud environment,untimely noise suppression of net-work data can directly reduce the effect of data deduplication.To improve the accuracy of data deduplication,this arti-cle put forward a network data deduplication algorithm in cloud environment based on autoregressive model.Firstly,a flexible spatial model of cloud environment was built.After determining the spatial autocorrelation measure of network data,the data denoising was completed.Based on the denoising result,the attribute features of network data in cloud environment were analyzed in detail.According to the extracted features,network redundant data was clustered.More-over,a prediction model of network redundant data was constructed by the autoregressive model,thus accurately pre-dicting and removing the network redundant data in cloud environment.Finally,network data was precisely dedupli-cated.The experimental results show that this method can effectively remove redundant data from network data during data deduplication,and has good deduplication effect.
Autoregressive modelCloud environmentNetwork dataDe-duplication algorithmRedundant data prediction model
NETL
NSTL
万方数据
维普
