A comparative study for massive data compression in long-distance distributed optical fiber sensing systems

With the growing demand for monitoring length and channel number of the fully distributed optical fiber sensors (DOFSs), the amount of sensing data is increasing rapidly, and there will be a heavy pressure for the massive data storage and transmission. In this paper, two lossless compression algorithms of Lempel-Ziv-Welch (LZW) and Huffman are comparatively studied to effectively compress the huge amount of data of typical DOFSs, e.g. Phi-OTDR, POTDR, and BOTDA systems. The comparison results show that the LZW based on dictionary has a better performance in the consuming time and compression ratio for the DOFS data.