面向物联网的目标导向型通信:系统设计与自适应资源优化

P. Lorenzo, M. Merluzzi, Francesco Binucci, Claudio Battiloro, P. Banelli, E. Strinati, S. Barbarossa
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引用次数: 0

摘要

物联网(IoT)应用集传感、无线通信、智能和执行于一体,实现了收集和处理大量数据的异构设备之间的互动。然而,物联网应用的有效性需要面对可用资源的限制,包括频谱、能源、计算、学习和推理能力。本文对物联网通信的主流方法提出了挑战,这种方法优先考虑资源的使用,以保证在比特级完美恢复传感器向中央单元传输的数据。我们提出了一种名为 "目标导向(GO)物联网系统设计 "的新方法,它超越了传统的比特相关指标,直接关注数据交换的目标实现情况。然后,通过整合传感、通信、计算、学习和控制的综合系统优化来实现改进。我们提供了数值结果,展示了我们的方法在边缘推理、合作传感和联合学习等引人注目的使用案例中的实际应用。这些例子突出了我们提出的方法的有效性和现实意义,有望彻底改变物联网系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Goal-Oriented Communications for the IoT: System Design and Adaptive Resource Optimization
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.
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