Graph Signal Processing (GSP) can be applied as a modeling tool to study and optimally configure IoT sensor networks. Such networks are often characterized by stringent power requirements and a high probability of sensor fault. In this scenario, understanding and governing the response on a sample of the sensors is critical to maximizing network lifetime and spreading out maintenance time. The aim of this paper is to verify the ability of the GSP to model and provide answers to these goals.
GSP based subsampling of IoT sensor networks
Sabatini A.;Vollero L.
2022-01-01
Abstract
Graph Signal Processing (GSP) can be applied as a modeling tool to study and optimally configure IoT sensor networks. Such networks are often characterized by stringent power requirements and a high probability of sensor fault. In this scenario, understanding and governing the response on a sample of the sensors is critical to maximizing network lifetime and spreading out maintenance time. The aim of this paper is to verify the ability of the GSP to model and provide answers to these goals.File in questo prodotto:
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