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Panalysis of the Efficiency of the VRS Algorithm in the Transmission of Weather Data

Year 2021, Volume: 16 , 98 - 105, 31.12.2021

Bojan Prlıncevıc Zoran Milivojević

https://doi.org/10.55549/epstem.1068560

Abstract

In the first part of this paper a Variable rate sampling, algorithm for prediction has been described. Variable rate sampling systems were used for reducing power demand, by reducing the number of sent samples. In the second part is performed an experiment where is tested algorithm for prediction of data for transmission and transmitted data. For the purpose of this analyze transmission and predictions are performed for temperatures, air pressure, wind speed, and visibility. Prediction on the side of the transmission is performed using three different extrapolations (mam, mab, and ng). At the receiving side reconstruction of the received signal is performed applying Linear, Cubic, Makima, and Spline extrapolations, built into Matlab. A simple reconstruction is also performed, using the last known value for prediction the next value (this prediction is in the paper named Step extrapolation). Objective quality measures SR (correlation coefficient of reducing the number of samples between a number of measured and transmitted samples), and MAE (mean absolute error between the measured and predicted values of temperatures, pressures and visibility values) were calculated. The results are presented in the table and graphically.

Keywords

VRS algorithm Efficiency Extrapolations Low power system

References

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  • https://www.infona.pl/resource/bwmeta1.element.elsevier-13f94baa-1d66-3bb8-b16f-fadc9b20042e.
  • Benini, L., Bogliolo, A., & De Micheli, G. (2000). A survey of design techniques for system-level dynamic power management. IEEE transactions on very large scale integration (VLSI) systems, 8(3), 299-316. https://ieeexplore.ieee.org/document/845896.
  • Irvine, G. B., Wang, L., Dickman, P., & Cumming, D. R. (2003). Variable-rate data sampling for low-power microsystems using modified Adams methods. IEEE transactions on signal processing, 51(12), 3182-3190. https://ieeexplore.ieee.org/document/1246524.
  • Mark, J., & Todd, T. (1981). A nonuniform sampling approach to data compression. IEEE Transactions on communications, 29(1), 24-32. https://ieeexplore.ieee.org/document/1094872.
  • Milivojević, Z. N., & Prlinčević, B. P. (2006). Analysis of the VRS prediction algorith at a low-power system.
  • Prlinčević, B. P., & Milivojević, Z. N. (2021, October). Section - information technology and mechanical engineering. http://vpts.edu.rs/sed/fajlovi/inf.pdf.
  • Rizvandi, N. B., Zomaya, A. Y., Lee, Y. C., Boloori, A. J., & Taheri, J. (2012). Multiple frequency selection in DVFS-enabled processors to minimize energy consumption. arXiv preprint arXiv:1203.5160.. https://researchers.mq.edu.au/en/publications/multiple-frequency-selection-in-dvfs-enabled-processors-to-minimi.
  • Srivastava, M. B., Chandrakasan, A. P., & Brodersen, R. W. (1996). Predictive system shutdown and other architectural techniques for energy efficient programmable computation. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 4(1), 42-55. https://ieeexplore.ieee.org/document/486080.
  • W. 2 U. (2020, September). Istorijski Meteorološki podaci beograd – synop. Weather2Umbrella ltd. https://www.weather2umbrella.com/istorijski-podaci-beograd-srbija-sr.
  • Wu, P. C., Kuo, Y. P., Wu, C. S., Chuang, C. T., Chu, Y. H., & Hwang, W. (2014, September). PVT-aware digital controlled voltage regulator design for ultra-low-power (ULP) DVFS systems. In 2014 27th IEEE International System-on-Chip Conference (SOCC) (pp. 136-139). IEEE. https://ieeexplore.ieee.org/document/6948914/.
  • Zhuo, C., Luo, S., Gan, H., Hu, J., & Shi, Z. (2019). Noise-aware DVFS for efficient transitions on battery-powered IoT devices. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(7), 1498-1510. https://ieeexplore.ieee.org/document/8718252.

Year 2021, Volume: 16 , 98 - 105, 31.12.2021

Bojan Prlıncevıc Zoran Milivojević

https://doi.org/10.55549/epstem.1068560

Abstract

References

  • Banerjee, A., Dhar, A. S., & Banerjee, S. (2001). FPGA realization of a CORDIC based FFT processor for biomedical signal processing. Microprocessors and Microsystems, 25(3), 131-142.
  • https://www.infona.pl/resource/bwmeta1.element.elsevier-13f94baa-1d66-3bb8-b16f-fadc9b20042e.
  • Benini, L., Bogliolo, A., & De Micheli, G. (2000). A survey of design techniques for system-level dynamic power management. IEEE transactions on very large scale integration (VLSI) systems, 8(3), 299-316. https://ieeexplore.ieee.org/document/845896.
  • Irvine, G. B., Wang, L., Dickman, P., & Cumming, D. R. (2003). Variable-rate data sampling for low-power microsystems using modified Adams methods. IEEE transactions on signal processing, 51(12), 3182-3190. https://ieeexplore.ieee.org/document/1246524.
  • Mark, J., & Todd, T. (1981). A nonuniform sampling approach to data compression. IEEE Transactions on communications, 29(1), 24-32. https://ieeexplore.ieee.org/document/1094872.
  • Milivojević, Z. N., & Prlinčević, B. P. (2006). Analysis of the VRS prediction algorith at a low-power system.
  • Prlinčević, B. P., & Milivojević, Z. N. (2021, October). Section - information technology and mechanical engineering. http://vpts.edu.rs/sed/fajlovi/inf.pdf.
  • Rizvandi, N. B., Zomaya, A. Y., Lee, Y. C., Boloori, A. J., & Taheri, J. (2012). Multiple frequency selection in DVFS-enabled processors to minimize energy consumption. arXiv preprint arXiv:1203.5160.. https://researchers.mq.edu.au/en/publications/multiple-frequency-selection-in-dvfs-enabled-processors-to-minimi.
  • Srivastava, M. B., Chandrakasan, A. P., & Brodersen, R. W. (1996). Predictive system shutdown and other architectural techniques for energy efficient programmable computation. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 4(1), 42-55. https://ieeexplore.ieee.org/document/486080.
  • W. 2 U. (2020, September). Istorijski Meteorološki podaci beograd – synop. Weather2Umbrella ltd. https://www.weather2umbrella.com/istorijski-podaci-beograd-srbija-sr.
  • Wu, P. C., Kuo, Y. P., Wu, C. S., Chuang, C. T., Chu, Y. H., & Hwang, W. (2014, September). PVT-aware digital controlled voltage regulator design for ultra-low-power (ULP) DVFS systems. In 2014 27th IEEE International System-on-Chip Conference (SOCC) (pp. 136-139). IEEE. https://ieeexplore.ieee.org/document/6948914/.
  • Zhuo, C., Luo, S., Gan, H., Hu, J., & Shi, Z. (2019). Noise-aware DVFS for efficient transitions on battery-powered IoT devices. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(7), 1498-1510. https://ieeexplore.ieee.org/document/8718252.
There are 12 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Bojan Prlıncevıc

Zoran Milivojević

Publication Date December 31, 2021
Published in Issue Year 2021Volume: 16

Cite

APA Prlıncevıc, B., & Milivojević, Z. (2021). Panalysis of the Efficiency of the VRS Algorithm in the Transmission of Weather Data. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 16, 98-105. https://doi.org/10.55549/epstem.1068560
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