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Leveraging sensor data content to assure sensor device trustworthiness in Mobile Edge Computing

机译:利用传感器数据内容来确保移动边缘计算中传感器设备的可信度

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摘要

One of the challenging characteristics of Fog and Mobile Edge Computing (FMEC) is the trustworthiness among the wireless sensor nodes. In FMEC, sensors participate in data analytics by collaborating with each other. Sensors are communicating as far as they are paired each other or the radio pipe addresses are matched. Once paired, microcontrollers units (MCUs) are allowed to transmit sensor data to a FMEC computing device. The trustworthiness of incoming sensor data is very significant to sensor data analytics. The sensor data trustworthiness determines the quality of the sensor data analytics and the accuracy of FMEC computing. However, the current techniques do not assure satisfactorily the trustworthiness of the sensors in part because MCUs are unexpectedly joining in and disappearing from FMEC computing. This paper proposes a new data approximation approach to train sensors, and to trigger for reputation and trustworthiness about sensor data. The contribution of this approach includes a sensor data content-driven trustworthiness assurance about participating sensor devices.
机译:雾和移动边缘计算(FMEC)的挑战性特征之一是无线传感器节点之间的可信赖性。在FMEC中,传感器通过相互协作来参与数据分析。传感器正在相互配对,或者无线电管道地址匹配。配对后,允许微控制器单元(MCU)将传感器数据传输到FMEC计算设备。传入传感器数据的可信赖性对于传感器数据分析非常重要。传感器数据的可信赖性决定了传感器数据分析的质量以及FMEC计算的准确性。但是,当前的技术不能令人满意地确保传感器的可信赖性,部分原因是MCU意外地加入了FMEC计算并从FMEC计算中消失了。本文提出了一种新的数据近似方法来训练传感器,并触发传感器数据的声誉和可信赖性。这种方法的贡献包括有关参与的传感器设备的传感器数据内容驱动的可信度保证。

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