Energy-Saving Forecasting Techniques for Measurement Data Transmitting WSNs

• Abstract:

  One of the most important reasons for the usage of relatively inexpensive energy-self-sufficient wireless sensor networks is their high reliability. Research in this particular field has been intensified recently. However, most of the proposed approaches have one problem in common: lifetime reduction due to an increased demand on data transmission or packet length. In this paper we propose a new technique for almost reversing the effects of this conflict by system identification and forecasting. Our work focuses on designing a close-to-perfect model for each sensor type and to use this for measurement data prediction. Then a data transmission is required only when the difference between the measured and predicted value exceeds a certain threshold. If, for example, every second prediction is true in this context, the lifetime of a wireless sensor node can be extended by more than 45 % while still constantly presenting accurate values to the user.
• Keywords:

  wireless sensor networks, system identification, forecasting, prediction, ARX, Kalman, energy-saving, lifetime extension
• Download:

  IMEKO-TC19-2014-028.pdf
• DOI:

  _unreg_tc19-2014.028

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