The pervasiveness of the smart Internet of Things (IoTs) enables many electric sensors and devices to be connected and generates a large amount of dataflow. Compared with traditional big data, the streaming dataflow is faced with representative challenges, such as high speed, strong variability, rough continuity, and demanding timeliness, which pose severe tests of its efficient management. In this paper, we provide an overall review of IoT dataflow management. We first analyze the key challenges faced with IoT dataflow and initially overview the related techniques in dataflow management, spanning dataflow sensing, mining, control, security, privacy protection, etc. Then, we illustrate and compare representative tools or platforms for IoT dataflow management. In addition, promising application scenarios, such as smart cities, smart transportation, and smart manufacturing, are elaborated, which will provide significant guidance for further research. The management of IoT dataflow is also an important area, which merits in-depth discussions and further study.
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