Fog computing with original data reference function

In recent years, since large amounts of data are being transferred to the cloud server because of the evolution of the Internet of Things (IoT), problems such as the network bandwidth restrictions and sensor feedback control delays have appeared. For these limitations, fog computing, in which the primary processing of sensor data is performed at the fog node, and only the results are transferred to the cloud server, has been proposed. However, in this method, when the original sensor data are necessary for the analysis in the cloud server, the data are missing. For this problem, I propose a data model, in which the original sensor data are stored at the fog node with a distributed database. Furthermore, the performance of this data model is evaluated, showing the original data reference from the cloud server can be executed efficiently, particularly in the case of installing multiple fog nodes.