• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.94-103
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• 2022

As a large amount of data generated by sensors or devices at the manufacturing site is transmitted to the server or client, problems arise in network processing time delay and storage resource cost increase. To solve this problem, considering the manufacturing site, where real-time responsiveness and non-disruptive processes are essential, QRC (Quotient Remainder Compression) and BL_beta compression algorithms that enable real-time and lossless compression were applied to actual manufacturing site sensor data for the first time. As a result of the experiment, BL_beta had a higher compression rate than QRC. As a result of experimenting with the same data by slightly adjusting the data size of QRC, the compression rate of the QRC algorithm with the adjusted data size was 35.48% and 20.3% higher than the existing QRC and BL_beta compression algorithms.