Label big data compression in Internet of things based on piecewise linearregression
- Autores: Ming Gu, Kun Zhang, Jianwel Zhao, Siddiq Babaker
- Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 1477-1486
- Idioma: inglés
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Resumen
In order to solve the key problem that most of the energy of wireless sensor network nodes is consumed inwireless data modulation, which is an extremely important and limited resource. The energy efficiencyevaluation scheme of data compression algorithm based on the separation of hardware factor and algorithmfactor is proposed; In order to improve the running efficiency of the compression algorithm and reduce the energy consumption of the algorithm itself, a program level energy-saving optimization method for the data compression algorithm is proposed; In order to keep the energy-saving benefits of the data compressionalgorithm when the wireless transmission power is adjusted, an adjustment mechanism of the compressionalgorithm which can adapt to the change of transmission power is proposed. The experiment shows that whenthe wireless transmission power is - 7dBm and below (k < 178.4), the data should be compressed by S-LZWalgorithm, and when the wireless transmission power is - 5dBm and above (k > 178.4), the b ~ RLE algorithmshould be used for compression. The validity of the method is verified.
