Lossless Compression Algorithm for Multi-source Sensor Data Research

DOI

10.2991/emim-17.2017.267How to use a DOI?

Keywords

Multi-source sensor; DEFLATE algorithm; Sub-search; Compression algorithm

Abstract

In recent years, multi-source sensor system has been widely used in military, agriculture, forestry and other fields, the diversity of information performance, the huge number of information, the complexity of information relations, and require information processing real-time, have been greatly Beyond the general computer integrated processing capacity. In this paper, studies have found that the DEFLATE algorithm is consistent with the "neighbor principle" of sensor data. This is a combination of LZ77 and Huffman algorithms, which in theory should deal with multi-source sensor data more effectively. This paper proposes to increase the "secondary search" function during the DEFLATE algorithm matching process. This improvement effectively increases the possibility of finding a longer matching string, thus further reducing the coding length.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Changchi Huang
AU  - Yuwen Chen
PY  - 2017/04
DA  - 2017/04
TI  - Lossless Compression Algorithm for Multi-source Sensor Data Research
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1324
EP  - 1331
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.267
DO  - 10.2991/emim-17.2017.267
ID  - Huang2017/04
ER  -