A Comparative Study of Lossless Compression Technique in Quantum Secure Direct Communication

This is a comparative study to explore the performance of three lossless compression techniques, namely Run Length Encoding (RLE), Shannon-Fano Coding (SFC), and Huffman Coding (HC) in the context of a Hybrid M-Ary in Braided Single Stage (HMBSS) protocol communication scheme. The previous study on HMBSS using HC found that HC's compression technique has drawbacks, i.e., it is sensitive to errors and noise in the transmission channel and limited to certain data types. These drawbacks did affect the value of the compression rate limit. In this study, we evaluate the effectiveness of RLE, SFC, and HC in terms of data size reduction, coding efficiency, and data transmission time by comparing their results arising from the simulation experiments using Python coding in Jupiter Notebook and developed based on the HMBSS protocol algorithm. This simulation experiment starts with an initial six randomly generated datasets. Each dataset is tested using three compression techniques, which resulted in 18 different datasets. The results from the experiments reveal that SFC and HC consistently achieved a higher compression ratio and coding efficiency than RLE. These two compression techniques' algorithms effectively reduce the data size while preserving the original information. In our study, we also find that the data transmission time is increased with larger text sizes for all three compression techniques. This indicates that the larger the data size, the more transmission time is required with regard to what the compression technique's algorithm is.

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Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/cybercomp60759.2024.10913632
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
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article

A Comparative Study of Lossless Compression Technique in Quantum Secure Direct Communication

Sofia Najwa Ramli, Nur Ziadah Harun, Nur Shahirah Azahari, Osman Ghazali et al.
Quantum Computing Algorithms and Architecture
article

A Comparative Study of Lossless Compression Technique in Quantum Secure Direct Communication

Sofia Najwa Ramli, Nur Ziadah Harun, Nur Shahirah Azahari, Osman Ghazali, Izlin Zuriani Ishak, Liew Seow Wooi
article en

Abstract

This is a comparative study to explore the performance of three lossless compression techniques, namely Run Length Encoding (RLE), Shannon-Fano Coding (SFC), and Huffman Coding (HC) in the context of a Hybrid M-Ary in Braided Single Stage (HMBSS) protocol communication scheme. The previous study on HMBSS using HC found that HC's compression technique has drawbacks, i.e., it is sensitive to errors and noise in the transmission channel and limited to certain data types. These drawbacks did affect the value of the compression rate limit. In this study, we evaluate the effectiveness of RLE, SFC, and HC in terms of data size reduction, coding efficiency, and data transmission time by comparing their results arising from the simulation experiments using Python coding in Jupiter Notebook and developed based on the HMBSS protocol algorithm. This simulation experiment starts with an initial six randomly generated datasets. Each dataset is tested using three compression techniques, which resulted in 18 different datasets. The results from the experiments reveal that SFC and HC consistently achieved a higher compression ratio and coding efficiency than RLE. These two compression techniques' algorithms effectively reduce the data size while preserving the original information. In our study, we also find that the data transmission time is increased with larger text sizes for all three compression techniques. This indicates that the larger the data size, the more transmission time is required with regard to what the compression technique's algorithm is.

Universiti Putra Malaysia (MY), Raffles University Iskandar (MY), Hospital Seberang Jaya (MY), Tun Hussein Onn University of Malaysia (MY), Northern University of Malaysia (MY)
Openalex Percentile: Top 74%
Quantum Computing Algorithms and Architecture
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