基于流量分析的XML嵌套数据流无损压缩算法

Research on lossless compression algorithm of XML nested data stream based on traffic analysis

为避免基体的反复压缩操作,提出一种基于流量分析的XML嵌套数据流无损压缩算法。利用GDDStream算法对高相似度的XML嵌套数据流进行聚类分析,并表述成“簇中心(基体)+个体差异量”形式,分解数据流,完成一次基体压缩;仅对差异量进行压缩,极大减少对基体的反复压缩操作;利用改进LZW算法实现XML嵌套数据流无损压缩。实验结果表明,压缩后不仅数据完整性得到了保证,数据量也大幅减少,数据冗余度降低,与压缩前数据相比,压缩后数据未出现变化,说明压缩算法性能较好。

In order to avoid repeated compression of the matrix,a lossless compression algorithm for XML nested data stream based on traffic analysis is proposed.The GDDStream algorithm is used to cluster the high similarity XML nested data stream,which is expressed in the form of “cluster center(matrix) + individual difference quantity”.The data stream is decomposed to complete one matrix compression.The compression towards difference quantity only could greatly reduces the repeated compression operation on the matrix,and the improved LZW algorithm could realize the lossless compression of XML nested data stream.The experiment results show that the data integrity could be guaranteed after compression and the data and the data redundancy has been reduced as well.Compared with the data before compression,the data after compression does not change,indicating that the compression algorithm has better performance.