Method and device for generating decision tree, method and device for message classification based on decision tree

Abstract

The invention discloses a decision tree generation method and equipment, and a decision tree-based message classification method and equipment. The decision tree generation method includes: transforming the rules in the original rule set into the range array of the decision tree; starting from the root node, cutting by combining multi-bit prefix and HiCuts algorithm until the number of rules in each node is less than the preset value. The message classification method based on the decision tree includes: extracting the source and destination IP addresses in the message, and converting them into a decision tree query array; starting from the root node to search, and searching in turn according to the cut dimension and the number of cuts, Until the leaf node is obtained; compare the message query array with the rules in the leaf node to obtain the rule matching the message. The present invention combines bit prefixes with HiCuts to generate a decision tree, reduces the depth of the decision tree, improves query efficiency and saves memory space when searching based on the decision tree.

Description

technical field [0001] The invention relates to the field of communications, and in particular, to a method and device for generating a decision tree, and a method and device for classifying messages based on a decision tree. Background technique [0002] With the development of network applications, today's network devices, such as routers, firewalls, and 3G network elements, usually need to support a series of functions such as access control, QOS (Quality of Service, quality of service), and policy routing. A common point of these functions is that they need to be classified according to the information of the packets, and then different types of packets need to be processed accordingly. Therefore, packet classification becomes a basic function of these devices. [0003] The realization of packet classification can usually be divided into: hardware way and software way. The hardware method needs to be implemented by special daughter cards or chips, and the price of thes...

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Problems solved by technology

The disadvantages of the algorithm are: the preprocessing process is very complicated (regardless of time and space); the memory space required by the algorithm is difficult to describe with expressions, and its size is related to the number N of rules in the rule set, the dimension k of the rules, and the number of rules. The degree of dispersion between

However, none of the above IPv4-based packet classification algorithms can be directly applied to IPv6 packet classification.

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