Double Index Data Compression Method for Onboard Computer
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TP311

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    Abstract:

    As the functions of on-board computer systems become more and more complex, the scale of programs is also growing rapidly. A stable and effective code compression function is required to ensure the storage and operation of on-board software under the background of extremely limited storage resources. Hybrid compression is currently the mainstream algorithm for lossless data compression, and it has the characteristics of high compression rate, large code size, and large demand for computing resources. However, embedded systems such as spaceborne computers require reliability and anti-jamming capabilities, and hybrid compression cannot play its amazing effect. At the same time, the compression rate of a single model is too low to meet the demand. This study proposes an improvement method based on the advantage of the low resource requirement of LZ77 algorithm, the details are as follows. The new algorithm uses a new matching record table for the compression. This table stores high-value indexes to assist in compression, which realizes the complementarity between the local advantages of the original algorithm and the global distribution of high-value data, and reduces data redundancy to a greater extent. In addition, the new algorithm combines dynamic filling, variable length coding, and other methods to further optimize the coding structure and reduce storage requirements. Finally, the lossless data compression algorithm (LZRC) is designed and implemented, which is more suitable for the aerospace field. Experimental results show that: (1) the code size of the new algorithm is 3.5 KB more than the code size of the original algorithm, and the average compression ratio of software has increased by 17%; (2) compared with hybrid compression, the runtime memory of the proposed algorithm is only 12%, and the code size is also reduced by 84%, which is more suitable for on-board computer systems.

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邓岸华,乔磊,杨孟飞.面向星载计算机的双重索引数据压缩方法.软件学报,2022,33(10):3844-3857

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History
  • Received:September 28,2020
  • Revised:January 06,2021
  • Online: October 13,2022
  • Published: October 06,2022
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