Compression Performance Analysis of Different File Formats

TL;DR

This study compares the compression performance of 22 different file formats using the Zlib algorithm, highlighting how some formats compress well while others do not, to optimize data storage and transmission efficiency.

Contribution

It provides a comprehensive analysis of compression gains across various file formats, guiding optimal format selection for data reduction.

Findings

Some file formats achieve significant size reduction and faster compression.

Certain formats show minimal compression gains and longer compression times.

The study offers recommendations for selecting file formats based on compression performance.

Abstract

In data storage and transmission, file compression is a common technique for reducing the volume of data, reducing data storage space and transmission time and bandwidth. However, there are significant differences in the compression performance of different types of file formats, and the benefits vary. In this paper, 22 file formats with approximately 178GB of data were collected and the Zlib algorithm was used for compression experiments to compare performance in order to investigate the compression gains of different file types. The experimental results show that some file types are poorly compressed, with almost constant file size and long compression time, resulting in lower gains; some other file types are significantly reduced in file size and compression time after compression, which can effectively reduce the data volume. Based on the above experimental results, this paper will then selectively reduce the data volume by compression in data storage and transmission for the file types in order to obtain the maximum compression yield.