Cun Ji

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The Internet of Things (IoT) brings traditional Internet industry and society with new trends and promising technologies. For industrial information with high amount and renewal speed characteristics, resulting in difficult data ingestion and analysis, this paper presented an Industrial Big Data ingestion and analysis Platform (IBDP). In the platform, we(More)
Despite having played a significant role in the Industry 4.0 era, the Internet of Things is currently faced with the challenge of how to ingest large-scale heterogeneous and multi-type device data. In response to this problem we present a heterogeneous device data ingestion model for an industrial big data platform. The model includes device templates and(More)
With the development of intelligent manufacturing technology, it can be foreseen that time series data generated by smart devices will raise to an unprecedented level. For time series with high amount, high dimension and renewal speed characteristics, resulting in difficult data mining and presentation on the original time series data. This paper presented(More)
The kNN join problem is to find the k nearest neighbors from a given dataset S for each point in the query set R. It is an operation required by many big data applications. As large volume of data are continuously generated in more and more real-life cases, we address the problem of monitoring kNN join results on data streams. Specifically, we are concerned(More)
In the case of a cloud-based remote control system such as SCADA (Supervisory Control and Data Acquisition) that enables users to collect data from cloud-connected machines deployed anywhere at any time. However, machine data models may not be updated in a timely manner after the devices are upgrades or modified. This leads to mismatches between the machine(More)
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