A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs

Wireless sensor networks (WSN) are groups of nodes that collectively sense and control an environment. The readings of these nodes may reach a point where it becomes too big for the network to handle, where data compression becomes an option to minimize the size of data being transmitted across the...

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Main Authors: Pastoral, Eugenio G., II, Maderazo, Rafael Nicholas E., Chua, Jeric Kerby G.
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語言:English
出版: Animo Repository 2022
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在線閱讀:https://animorepository.dlsu.edu.ph/etdb_comtech/1
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1000&context=etdb_comtech
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spelling oai:animorepository.dlsu.edu.ph:etdb_comtech-10002022-09-14T03:26:56Z A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs Pastoral, Eugenio G., II Maderazo, Rafael Nicholas E. Chua, Jeric Kerby G. Wireless sensor networks (WSN) are groups of nodes that collectively sense and control an environment. The readings of these nodes may reach a point where it becomes too big for the network to handle, where data compression becomes an option to minimize the size of data being transmitted across the network. LZMA, LZW, LEC, gzip, and bzip2 are well-known lossless compression techniques used in prior studies and are generally recommended for sensor data. Previous studies show that these algorithms yielded at least 60% in compression ratio. This study simulated data compression in a WSN using these algorithms with a Raspberry Pi, ZigBee module, and a personal computer to reproduce the functionalities of a WSN. The simulated scenarios reveal that bzip2 and LZMA are suited for sensor data compression, followed by LZW and gzip, and LEC performing the worst, with all results compared to prior studies. 2022-07-08T07:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdb_comtech/1 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1000&context=etdb_comtech Computer Technology Bachelor's Theses English Animo Repository Wireless sensor networks Data compression (Computer science) Information Security
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Wireless sensor networks
Data compression (Computer science)
Information Security
spellingShingle Wireless sensor networks
Data compression (Computer science)
Information Security
Pastoral, Eugenio G., II
Maderazo, Rafael Nicholas E.
Chua, Jeric Kerby G.
A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
description Wireless sensor networks (WSN) are groups of nodes that collectively sense and control an environment. The readings of these nodes may reach a point where it becomes too big for the network to handle, where data compression becomes an option to minimize the size of data being transmitted across the network. LZMA, LZW, LEC, gzip, and bzip2 are well-known lossless compression techniques used in prior studies and are generally recommended for sensor data. Previous studies show that these algorithms yielded at least 60% in compression ratio. This study simulated data compression in a WSN using these algorithms with a Raspberry Pi, ZigBee module, and a personal computer to reproduce the functionalities of a WSN. The simulated scenarios reveal that bzip2 and LZMA are suited for sensor data compression, followed by LZW and gzip, and LEC performing the worst, with all results compared to prior studies.
format text
author Pastoral, Eugenio G., II
Maderazo, Rafael Nicholas E.
Chua, Jeric Kerby G.
author_facet Pastoral, Eugenio G., II
Maderazo, Rafael Nicholas E.
Chua, Jeric Kerby G.
author_sort Pastoral, Eugenio G., II
title A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
title_short A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
title_full A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
title_fullStr A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
title_full_unstemmed A comprehensive review and performance evaluation of modern lossless compression algorithms for real-time WSNs
title_sort comprehensive review and performance evaluation of modern lossless compression algorithms for real-time wsns
publisher Animo Repository
publishDate 2022
url https://animorepository.dlsu.edu.ph/etdb_comtech/1
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1000&context=etdb_comtech
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