With the fast development of Industrial Internet of Things (IIoT), a large amount of data is being generated continuously by different sources. Storing all the raw data in the IoT devices locally is unwise considering that the end de-vices' energy and storage spaces are strictly limited. In addition, the devices are unreliable and vulnerable to many threats be-cause the networks may be deployed in remote and unattended areas. In proposed system we discuss the emerging challenges in the aspects

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... f data processing, secure data storage, efficient data retrieval and dynamic data collection in IoT. Then, we design a flexible and economical framework to solve the problems above by integrating the fog computing and cloud computing. Based on the time latency requirements, the collected data are processed and stored in the cloud server. Specifically, all the raw data are first preprocessed and then the time-sensitive data (e.g., control information) are used and stored locally. The non-time-sensitive data (e.g., monitored data) are transmitted to the cloud server to support data retrieval and mining in the future.