A Survey of Data Compression Algorithms and their Applications

TL;DR

This survey reviews various data compression algorithms, their performance, applications, and recent research challenges, highlighting their importance in reducing storage and bandwidth needs in modern data transmission and storage.

Contribution

It provides a comprehensive overview of key data compression algorithms, evaluating their performance and discussing current issues and recent research developments.

Findings

Different algorithms vary in compression efficiency and speed

Data compression significantly reduces storage and bandwidth usage

Recent research focuses on improving compression ratios and computational efficiency

Abstract

Today, with the growing demands of information storage and data transfer, data compression is becoming increasingly important. Data Compression is a technique which is used to decrease the size of data. This is very useful when some huge files have to be transferred over networks or being stored on a data storage device and the size is more than the capacity of the data storage or would consume so much bandwidth for transmission in a network. With the advent of the Internet and mobile devices with limited resources, data compression has gained even more importance. It can be effectively used to save both storage and bandwidth, thus to decrease download duration. Data compression can be achieved by a host of techniques. During this survey, I'm going to thoroughly discuss some of important data compression algorithms, their performance evaluation, and their major applications along with today's issues and recent research approaches.