Mass data storage and sharing algorithm in distributed heterogeneous environment

Abstract

In the distributed heterogeneous environment, mass data is stored in the database in the form of cloud storage, in order to improve the throughput performance of mass data storage, a mass data storage and sharing algorithm in distributed heterogeneous environment is proposed based on piecewise linear fusion equilibrium scheduling. The distributed heterogeneous environment of mass data storage is constructed, and the design of storage nodes localization is optimized, association rule feature of mass data in distributed heterogeneous environment is extracted, and the fuzzy C means clustering method is used to classify the extracted features. A piecewise linear data fusion is realized in high dimension phase space to improve the performance of equalization data storage channel, distributed storage and resource sharing of massive data in the transmission link layer are obtained. The simulation results show that throughput performance is better with this method in mass data storage, the bit amount of stored data is increased, the classification accuracy of mass data in storage space is high, and it can improve the security of massive data storage.

Keywords:

• Distributed heterogeneous environment
• Massive data
• Storage
• Clustering
• Fuzzy C mean
• Information fusion