Graph Signal Processing for IoT Sensor Networks

Anna Sabatini

doi:10.1109/COMPSAC54236.2022.00264

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Graph Signal Processing for IoT Sensor Networks

2022-06-01

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Anna Sabatini *

Luca Vollero

DOI：10.1109/COMPSAC54236.2022.00264

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Abstract

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IoT sensors networks are often characterized by stringent power requirements and a high probability of sensor fault. This paper, thanks to Graph Signal Processing (GSP), aims to model an IoT scenario to find an optimal sensor configuration for battery-saving applications. In detail, the Girwan Newman method is applied to the graph to find clusters and the performance of the described method is evaluated in terms of signal-noise ratio depending on the fraction of sampled sensors. Tests were performed both on simulated data and real data from the European Environment Agency considering several air pollutants concentrations.

Keywords:

GSP

IoT

sampling and interpolation