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An Empirical Analysis on Lossless Compression Techniques

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Computer and Communication Engineering (CCCE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1823))

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Abstract

A method of presenting source data into it’s compact form is known as data compression. In this process, data size is minimized, redundancy is eliminated, and excess information is gotten rid of. A reduction in actual data is usually advantageous because it uses less resources overall, including bandwidth, processing, space, time, and many others. There are numerous compression algorithms for reducing the size of data of different formats. Even for compressing a particular data type, many approaches are being used. The proposed research has explored three of the lossless compression techniques which are: Run Length Encoding, Lempel Ziv Welch, and Huffman Encoding algorithms. We found out that based on compression size, compression ratio, and space saving percentage, Lempel Ziv Welch outperformed the other two. In contrast, Huffman Encoding performed better than the other two based on compression time. In the best case, LZW got a compression size of 250992 bytes, a compression ratio of 5.0106, and a space saving percentage of 80.04% while Huffman encoding got a compression time of 32.28 ms.

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Authors and Affiliations

  1. BRAC University, 66 Mohakhali, Dhaka, Bangladesh

    Mohammad Badrul Hossain & Md. Nowroz Junaed Rahman

Authors
  1. Mohammad Badrul Hossain
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  2. Md. Nowroz Junaed Rahman
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Correspondence to Mohammad Badrul Hossain .

Editor information

Editors and Affiliations

  1. University of Naples Federico II, Naples, Italy

    Filippo Neri

  2. Concordia University, Montreal, QC, Canada

    Ke-Lin Du

  3. The University of New South Wales, Sydney, NSW, Australia

    Vijayakumar Varadarajan

  4. Miguel Hernández University of Elche, Elche, Spain

    Angel-Antonio San-Blas

  5. Northwestern Polytechnical University, Xi'an, China

    Zhiyu Jiang

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Hossain, M.B., Rahman, M.N.J. (2023). An Empirical Analysis on Lossless Compression Techniques. In: Neri, F., Du, KL., Varadarajan, V., San-Blas, AA., Jiang, Z. (eds) Computer and Communication Engineering. CCCE 2023. Communications in Computer and Information Science, vol 1823. Springer, Cham. https://doi.org/10.1007/978-3-031-35299-7_13

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  • DOI: https://doi.org/10.1007/978-3-031-35299-7_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35298-0

  • Online ISBN: 978-3-031-35299-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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