Efficient and Real-Time Compression Schemes of Multi-Dimensional Data from Ocean Buoys Using Golomb-Rice Coding

Quan Liu, Ziling Huang, Kun Chen () and Jianmin Xiao
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Quan Liu: School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Ziling Huang: School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Kun Chen: School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Jianmin Xiao: School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China

Mathematics, 2025, vol. 13, issue 3, 1-17

Abstract: The energy supply of ocean monitoring buoys is a major challenge, especially for long-term, low-power applications. Data compression can reduce transmission energy and extend system lifespan. In particular, the algorithm cannot introduce delays to ensure real-time monitoring. In this scenario, we propose an efficient real-time compression scheme for lossless data compression (ERCS_Lossless) based on Golomb-Rice coding to efficiently compress each dimensional data independently. Additionally, we propose an efficient real-time compression scheme for lossy data compression with a flag mechanism (ERCS_Lossy_Flag), which incorporates a flag bit for each dimension, indicating if the prediction error exceeds a threshold, followed by further compression using Golomb-Rice coding. We conducted experiments on 24-dimensional weather and wave element data from a single buoy, and the results show that ERCS_Lossless achieves an average compression rate of 47.40%. In real communication scenarios, splicing and byte alignment operations are performed on multidimensional data, and the results show that the variance of the payload increases but the mean decreases after compression, realizing a 38.60% transmission energy saving, which is better than existing real-time lossless compression methods. In addition, ERCS_Lossy_Flag further reduces the amount of data and improves energy efficiency when lower data accuracy is acceptable.

Keywords: multidimensional data; real-time compression; Golomb-Rice coding; energy saving (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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