Network traffic scheduling system and method based on DPI and machine learning
A technology of network traffic and machine learning, applied in the field of computer networks, can solve problems such as difficult global forms, lagging new applications, and unrecognizable encrypted network data streams, etc., to achieve reasonable business processing, high network utilization, and fast The effect of positioning
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[0038] The description of the following embodiments refers to the accompanying drawings to illustrate specific embodiments in which the present invention can be implemented.
[0039] Please refer to figure 1 As shown, Embodiment 1 of the present invention provides a network traffic scheduling system based on DPI and machine learning, including:
[0040] The SDN controller, data analysis server, data collection server and physical equipment based on the SDN architecture are interconnected by several physical equipment to form a data transmission network;
[0041] The SDN controller is used to implement the forwarding link planning of the network data by issuing commands and rules to physical devices, and at the same time it monitors the network environment of the data transmission network;
[0042] The physical device is used to identify and mark the network access data, and forward the network access data according to the commands and rules; the mark is set by the SDN controller for di...
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