一种适于时空大数据的有损压缩算法

A Lossy Compression Algorithm for Big Spatio-Temporal Data

随着时空大数据的爆炸式增长,给数据存储带来高额的成本。为节省存储资源,提出一种基于欧氏距离的几何中心提取压缩的算法。实验结果表明,该算法通过几何中心坐标作为数据特征点,能够有效对时空大数据进行高效压缩,具有较高压缩比,且解压后的数据准确有效。

As The explosion of the big data, data storage to bring the high cost, in order to save storage resources, proposes a geometric center extraction and compression algorithm based on Euclidean distance. The algorithm through the geometric center coordinates as data feature points, can effectively compress the big data effectively, has higher compression ratio, and extract the data accurate and effective.