DETERMINING OPTIMAL COMPRESSION ALGORITHM FOR FILES OF DIFFERENT FORMATS

Authors

DOI:

https://doi.org/10.35546/kntu2078-4481.2024.2.17

Keywords:

algorithm, compression, encoding, Shannon-Fano, Huffman, RLE, LZ78.

Abstract

The aim of the article is to highlight possible areas of the use of compression algorithms in various fields. The article investigates the efficiency of the compression of files of different formats and provides recommendations on the optimal compression algorithms for specific scenarios. The research was carried out empirically: compression algorithms were implemented at the software level, the programs were used to compress files of various formats, the size of the resulting files was determined, and a comparison of the efficiency of the methods was made. Research results. The article presents a table of file sizes after compression using different compression algorithms, calculates compression ratios for each case, determines the average compression ratios for each compression algorithm, analyses the efficiency of compression algorithms, and identifies the optimal compression algorithms for files of different formats. The scientific novelty of this work is an integrated approach to comparing compression algorithms by compression ratios on different file formats and the study of the combination of Huffman and LZ78 algorithms, which has not been widely studied before. This allows us to gain a deeper understanding of the process of compressing files of different formats and identify effective algorithms for specific data types. The analysis can contribute to the development and improvement of file compression methods and have practical applications in various fields, such as data storage and transmission, file compression, and improving the performance of information processing systems. The practical significance of the work lies in its potential usefulness for various fields. It provides recommendations and conclusions on the selection of efficient file compression algorithms for different file formats. This can have a positive impact on data storage and transmission, data processing speed, software development, and multimedia data. Using optimal compression algorithms helps reduce file size, saves resources, and improves user experience.

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Published

2024-07-01