Message classifying method based on rule information entropy

A message classification and information entropy technology, applied in the field of communication, can solve the problems of slow response speed, high time complexity, and difficulty in adapting to high-speed linear forwarding of the network, and achieve the effect of increasing speed, narrowing the matching range, and facilitating fast forwarding

Inactive Publication Date: 2014-05-21
SOUTHWEST UNIVERSITY
View PDF1 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

So far, some fast routing table lookup algorithms have been developed, but there are still slow response speeds, high time complexity, and it is difficult to adapt to the high-speed linear forwarding of the network, which has become the bottleneck of network transmission.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Message classifying method based on rule information entropy
  • Message classifying method based on rule information entropy
  • Message classifying method based on rule information entropy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] The technical solutions of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] The present invention calculates the outlier attribute subset of the rule on the attribute field of the message classification rule through the preprocessing of the classification rule, and then uses the attribute weight vector of the rule to calculate the weighted distance, and then analyzes the subspace distance of the weighted neighborhood of the rule. Group impact factor, which generates a frequent matching subset of message matching by comparing with the outlier factor threshold. Subsequent packet matching first matches the frequently matched subset of rules with non-outlier attributes, which improves the matching efficiency. At the same time, the time cost of the frequent matching subset generated by the preprocessing of the classification rule is smaller than the matching cost of the whole data...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a message classifying method based on rule information entropy. The message classifying method based on the rule information entropy includes: calculating regular stray attribute subsets on an attribute domain with regular classified messages through preprocessing on classification rules, using a regular attribute weight vector to calculate weighting distance afterwards, and then analyzing subspace straying influence factors of regular weighting neighbor domains, and generating frequent matching subsets for matching messages by comparing the subspace straying influence factors with straying factor threshold value. According to the message classifying method based on the rule information entropy, subsequent message matching had the regular frequent matching subsets with no-straying attributes by being compared with prior message matching, matching efficiency is improved, and simultaneously time expenditure for generating the frequent matching subsets through the preprocessing of the classification rules is smaller than time expenditure for matching a whole data stream, and transmission performance of an algorithm used in the message classifying method is higher than transmission performance of the algorithm before the preprocessing.

Description

technical field [0001] The invention belongs to the technical field of communication, and relates to a message classification method based on rule information entropy. Background technique [0002] With the rapid development of Internet applications, the population of Internet users is rapidly expanding on an unprecedented scale. The advent of the Internet age has provided infinite convenience for people's life, but at the same time, it has also posed huge challenges to the network bandwidth, network security, and network service types. Compared with the original network application, the business types supported by the network have also changed from traditional data services to personal multimedia services, corporate financial services, and government office applications. Therefore, through effective technical means, management and control of various business flows in the network, allocation of reasonable bandwidth resources for different applications, and provision of diff...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24
Inventor 陈善雄熊海灵伍胜于显平
Owner SOUTHWEST UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products