Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and process considerable amounts of data. However, the effectiveness of IoT applications needs to face the limitation of available resources, including spectrum, energy, computing, learning and inference capabilities. This article challenges the prevailing approach to IoT communication, which prioritizes the usage of resources in order to guarantee perfect recovery, at the bit level, of the data transmitted by the sensors to the central unit. We propose a novel approach, called goal-oriented (GO) IoT system design, that transcends traditional bit-related metrics and focuses directly on the fulfillment of the goal motivating the exchange of data. The improve-ment is then achieved through a comprehensive system optimization, integrating sensing, communication, computation, learning, and control. We provide numerical results demonstrating the practical applications of our methodology in compelling use cases such as edge inference, cooperative sensing, and federated learning. These examples highlight the effectiveness and real-world implications of our pro-posed approach, with the potential to revolutionize IoT systems.

Goal-Oriented Communications for the IoT: System Design and Adaptive Resource Optimization / Di Lorenzo, Paolo; Merluzzi, Mattia; Binucci, Francesco; Battiloro, Claudio; Banelli, Paolo; Strinati, Emilio Calvanese; Barbarossa, Sergio. - In: IEEE INTERNET OF THINGS MAGAZINE. - ISSN 2576-3180. - 6:4(2023), pp. -32. [10.1109/iotm.001.2300163]

Goal-Oriented Communications for the IoT: System Design and Adaptive Resource Optimization

Di Lorenzo, Paolo;Merluzzi, Mattia;Battiloro, Claudio;Banelli, Paolo;Barbarossa, Sergio
2023

Abstract

Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and process considerable amounts of data. However, the effectiveness of IoT applications needs to face the limitation of available resources, including spectrum, energy, computing, learning and inference capabilities. This article challenges the prevailing approach to IoT communication, which prioritizes the usage of resources in order to guarantee perfect recovery, at the bit level, of the data transmitted by the sensors to the central unit. We propose a novel approach, called goal-oriented (GO) IoT system design, that transcends traditional bit-related metrics and focuses directly on the fulfillment of the goal motivating the exchange of data. The improve-ment is then achieved through a comprehensive system optimization, integrating sensing, communication, computation, learning, and control. We provide numerical results demonstrating the practical applications of our methodology in compelling use cases such as edge inference, cooperative sensing, and federated learning. These examples highlight the effectiveness and real-world implications of our pro-posed approach, with the potential to revolutionize IoT systems.
2023
Goal-Oriented communications , edge AI, system optimization
01 Pubblicazione su rivista::01a Articolo in rivista
Goal-Oriented Communications for the IoT: System Design and Adaptive Resource Optimization / Di Lorenzo, Paolo; Merluzzi, Mattia; Binucci, Francesco; Battiloro, Claudio; Banelli, Paolo; Strinati, Emilio Calvanese; Barbarossa, Sergio. - In: IEEE INTERNET OF THINGS MAGAZINE. - ISSN 2576-3180. - 6:4(2023), pp. -32. [10.1109/iotm.001.2300163]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1702771
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