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

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.