The Optimized Cloud Storage Method of Massive GNSS Small Files

The data volume of GNSS is increasing exponentially, while HDFS is capable of handling the problem of the storage bottleneck of massive GNSS data, it is faced with much time consumption, poor file correlation and lack of optimization mechanisms. According to the matter of the low processing efficiency of massive GNSS small files faced by HDFS, a new cloud storage method is provided based on the types, characteristics and storage flow of GNSS data, the writing, adding, reading and deleting strategies are optimized. First the observation files and solution files are respectively merged, and the compressed Trie index is established on the merged files; and after splitting the existed index, the index blocks are distributed stored in each mode based on the matching algorithm. Data and products of 28 days from IGS are applied in the experiment, and the result shows that the memory consumption of each node can be decreased greatly, and the efficiency of writing, direct reading, reading after adding files, concurrent reading and deleting can be improved significantly, effective cloud storage of massive GNSS small files is hereafter realized.