Flow segmentation method and system

Abstract

The invention relates to the field of Internet technologies, and discloses a flow segmentation method and a flow segmentation system. The method comprises the steps of receiving a flow segmentation request, and acquiring information of flow to be segmented in the request; selecting a search random tree according to the information of the flow to be segmented; determining a segmentation condition value of the flow to be segmented according to the information of the flow to be segmented, and searching a match in the search random tree; and determining a flow distribution mode for the flow to be segmented according to a match searching result and a branch matched with the segmentation condition value, and processing the flow to be segmented according to the flow distribution mode. According to the technical scheme of the method and system of the invention, the efficient and flexible flow segmentation is achieved by combination of tree-shaped search and random search.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a traffic segmentation method and system. Background technique [0002] After the development of new functions or new strategies, Internet sites need to conduct a small-scale test and evaluation before going online with full traffic. In order to fully evaluate the pros and cons of new functions or new strategies as much as possible, it is often necessary to test in the actual network environment , the efficiency and flexibility of test evaluation have an essential impact on system operation. For example, the demand-side platform (Demand-Side Platform, DSP) system of Internet advertising is a system that needs to be dynamically adjusted at any time. During the development and operation of the system, some business functions and requirements need to be continuously launched. The impact on the entire system is very large. If you go online directly, unexpected online pr...

AI Technical Summary

Problems solved by technology

[0005] However, whether it is random probability segmentation or hash segmentation, the actual traffic processing is a very rough segmentation method. These segmentation methods ignore the characteristics of the traffic itself, and segment the traffic as undifferentiated data in a single way. Processing is an extensive resource segmentation method

Although the existing traffic segmentation method is simple and primitive, it is easy to implement, but the existing method can no longer meet the needs of traffic classification users

Furthermore, the existing traffic segmentation methods are flat and can only achieve fixed-level traffic segmentation. This segmentation method is difficult to configure flexibly, and its readability and maintainability are very poor. To come up with an effective segmentation method that meets actual needs requires manual writing of a large amount of cumbersome and repetitive configuration information

Images