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Data compression algorithms for wireless sensor networks: a review and comparison

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dc.contributor.author Ketshabetswe, Keleadile Lucia
dc.contributor.author Zungeru, Adamu Murtala
dc.contributor.author Mtengi, Bokani
dc.contributor.author Lebekwe, Caspar K.
dc.contributor.author Prabaharan, S.R.S.
dc.date.accessioned 2022-06-14T13:17:36Z
dc.date.available 2022-06-14T13:17:36Z
dc.date.issued 2021-09-29
dc.identifier.citation Ketshabetswe, K. L. et al . (2022) Data compression algorithms for wireless sensor networks: a review and comparison. IEEE Access, 9, 136872-136891. 10.1109/ACCESS.2021.3116311. en_US
dc.identifier.issn 2666-0164
dc.identifier.uri http://repository.biust.ac.bw/handle/123456789/453
dc.description.abstract Energy consumption has risen to be a bottleneck in wireless sensor networks. This is caused by the challenges faced by these networks due to their tiny sensor nodes that have limited memory storage, small battery capacity, limited processing capability, and bandwidth. Data compression has been used to reduce energy consumption and improve network lifetime, as it reduces data size before it can be forwarded from the sensing node to the sink node in the network. In this paper, a survey and comparison of currently available data compression techniques in wireless sensor networks are conducted. Suitable sets of criteria are defined to classify existing data compression algorithms. An adaptive lossless data compression algorithm (ALDC) is analyzed through MATLAB coding and simulation from the reviewed data compression techniques. The analysis aims to discover strategies that can be used to reduce the amount of data further before it is transmitted. From this analysis, it was discovered that encoding residue samples, rather than raw data samples, reduced the bitstream from 112 bits to a range of 30 to 36 bits depending on the sample block sizes. The average length of data samples to be passed to the encoder was minimized from the original 14 bits per symbol to 1.125 bits per symbol. This demonstrated a 0.875 code efficiency or redundancy. It resulted in an energy saving of 67.8% to 73.2%. This work further proposes a data compression algorithm that encodes the residue samples with fewer bits than the ALDC algorithm. The algorithm reduced the bitstream to 26 bits. The average length of the code is equal to the entropy of the data samples, demonstrating zero redundancy and an improved energy saving of 76.8% compared to ALDC. The proposed algorithm, therefore, shows improved energy efficiency through data compression. en_US
dc.description.sponsorship This work was supported by the Office of Research, Development, and Innovation (ORDI) of Botswana International University of Science and Technology under Grant S00297. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Compression ratio en_US
dc.subject Data aggregation en_US
dc.subject Data compression en_US
dc.subject Wireless sensor networks en_US
dc.title Data compression algorithms for wireless sensor networks: a review and comparison en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department cte en_US


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