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METHOD OF INTELLIGENT QUASI-INDIFFERENT DATA AGGREGATION IN HETEROGENEOUS WIRELESS SENSOR NETWORKS

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A new method for intelligent quasi-indifferent data aggregation of heterogeneous wireless sensor networks is presented. The essence of the method consists in converting the initial vectors of values recorded by the sensor nodes to vectors of values of the coefficients of piecewise polynomial regression containing a smaller number of elements, as well as in forming them into groups by calculating the Chebyshev distance with subsequent comparison with a threshold value. The developed method includes the stage of data adaptation to anomalies, which is provided by calculating and comparing with the threshold value of the scaled mean absolute deviation. The method is focused on the use in the hardware and software logic of local computing devices — sensor nodes — and can serve as a basis when designing various routing protocols for heterogeneous wireless sensor networks.

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