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Data reduction in sensor networks based on dispersion analysis

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Abstract

Wireless sensor networks are commonly used to collect observations of real-world phenomena at regular time intervals. Sensor nodes rely on limited power sources, and some studies indicate that the main source of energy consumption is related to data transmissions. In this paper, we propose an approach to reduce data transmissions in sensor nodes based on data dispersion analysis. This approach aims to avoid transmitting measurements whose values present low dispersion while keeping low CPU utilization rate. Performance evaluation results obtained by the Castalia simulator confirm that the results were promising in reducing data transmissions while maintaining significantly low processing time, data accuracy and low energy consumption.

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Notes

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    https://archive.ics.uci.edu/ml/datasets.html.

  2. 2.

    https://github.com/boulis/Castalia.

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    http://www.ti.com/product/CC2420.

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Correspondence to Janine Kniess.

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Kniess, J., Oliveira, S. Data reduction in sensor networks based on dispersion analysis. Computing (2020). https://doi.org/10.1007/s00607-020-00795-9

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Keywords

  • Data reduction
  • Sensor networks
  • Dispersion analysis
  • Internet of things

Mathematics Subject Classification

  • 68Mxx
  • 68M01