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Fog computing with original data reference function

机译:具有原始数据参考功能的雾计算

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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.
机译:近年来,由于由于物联网(IoT)的发展将大量数据传输到云服务器,因此出现了诸如网络带宽限制和传感器反馈控制延迟之类的问题。由于这些限制,已经提出了雾计算,在雾计算中,传感器数据的主要处理在雾节点上进行,仅将结果传输到云服务器。但是,在这种方法中,当原始传感器数据对于云服务器中的分析是必需的时,该数据将丢失。针对此问题,我提出了一种数据模型,其中原始传感器数据通过分布式数据库存储在雾节点处。此外,评估了此数据模型的性能,显示可以有效执行来自云服务器的原始数据引用,特别是在安装多个雾节点的情况下。

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