Abstract
Large networks of IoT devices, each consisting of one or more sensors, are being increasingly deployed for comprehensive real-time monitoring of cyber-physical systems. Such networks form an essential component of the emerging edge computing paradigm and are expected to increase in complexity and size. The physical phenomenon sensed by different sensors (within the same or different IoT devices in close proximity) often have relationships that makes them correlated. This is a form of proxy sensing that can be exploited for achieving better energy efficiency and higher robustness in monitoring. In this article, we explore how a set of sensors can optimize its data collection rates efficiently in a semi-distributed manner and yet provide the advantages of autonomy, relative isolation, and distributed control that is essential in a large-scale network.
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