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在云计算环境下,传统的光纤数据存储方式对于规模较大的海量光纤通信数据很难进行实时传输和调度,对海量光纤通信数据的存储,存在一定的存储负荷问题。提出一种基于自适应子空间特征压缩算法的通信数据存储模型,分析数据的特征,采用滤波算法过滤冗余的数据,通过自适应子空间特征压缩算法降低海量光纤数据存储的负荷,进一步实现对海量光纤通信数据存储模型的优化。实验仿真结果表明,改进后的方法对海量光纤通信数据存储,有效提高海量光纤数据的传输和利用率,降低了存储负荷且具有较好的实用性。
In the cloud computing environment, the traditional optical fiber data storage method is difficult to transmit and dispatch real-time data for the large-scale mass optical fiber communication data, and there is a certain storage load problem for mass optical fiber communication data storage. A communication data storage model based on adaptive subspace feature compression algorithm was proposed. The data characteristics were analyzed. Filtering redundant data by filtering algorithm and reducing the load of mass optical data storage by adaptive subspace feature compression algorithm, Optimization of Mass Fiber Optic Communication Data Storage Model. The experimental results show that the improved method can save mass data transmission and utilization of optical fiber, reduce the storage load and have good practicability.