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A Governance Architecture for Self-Adaption Control in IoT Applications

机译:IOT应用中自适应和控制的治理架构

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The “Internet of Things” has become a reality with projections of 28 billion connected devices by 2021. Much R&D is currently focused on creating methods to efficiently handle an influx of data. Flow based programming, where data is moved through a network of processes, is a model well suited to IoT. This paper proposes a dynamic, distributed data processing architecture, utilizing a flow based programming inspired approach. We illustrate a distributed configuration management protocol, which coordinates processing between edge devices and a central controller. Our proposed architecture is evaluated in a vehicle use case that predicts driver alertness. We present a scenario for reducing data on vehicular networks when the connectivity options are limited, while maintaining computational accuracy.
机译:“事物互联网”已成为2021年的预测的一个现实,通过2021年的预测。很多研发目前专注于创造有效处理数据涌入的方法。基于流程的编程,其中数据通过流程网络移动,是一个适合IOT的模型。本文提出了一种流动分布式数据处理架构,利用基于流的编程灵感方法。我们说明了分布式配置管理协议,其协调边缘设备和中央控制器之间的处理。我们所提出的架构在预测驱动程序警报的车辆用例中进行评估。当连接选项有限时,我们展示了减少车辆网络上的数据的场景,同时保持计算精度。

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