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Method for realizing fuzzy neuron active queue management method in IPCOP

An active queue management and neuron technology, applied in the field of fuzzy neuron active queue management in IPCOP, can solve problems such as limited effectiveness, no application, complex and changeable network, etc., and achieve the effect of small queue volatility

Inactive Publication Date: 2012-12-12
JILIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In order to improve the overall performance of the system, a differential link is added on the basis of PI. For example, PD and PID appear as an AQM algorithm to adjust the queue length. However, due to the delay and randomness of the computer network itself, these The handling effect of the controller is not very ideal
Moreover, it is problematic and impractical to treat the network as a linear time-invariant system, because the actual network is complex and changeable
Therefore, these methods have limited effectiveness, and these algorithms are implemented in NS2 simulation software, and have not been applied in the actual network environment

Method used

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  • Method for realizing fuzzy neuron active queue management method in IPCOP
  • Method for realizing fuzzy neuron active queue management method in IPCOP
  • Method for realizing fuzzy neuron active queue management method in IPCOP

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Embodiment Construction

[0065] The present invention is described in detail below in conjunction with accompanying drawing:

[0066] refer to figure 2 , the technical problem solved by the present invention is to add the fuzzy neuron method to the IPCOP software router and apply it in the actual network environment. The fuzzy neuron method can adjust the queue length according to the expected value, and finally the instantaneous queue length can be stabilized at the Near the expected value, and the queue fluctuation is small, the method that the fuzzy neuron active queue management method of the present invention realizes in IPCOP comprises the following steps:

[0067] 1. Definition and initialization of relevant parameters:

[0068] 1) limit is the router cache size, the initial value is 600packets;

[0069] 2) q ref is the expected value of the queue length, the initial value is 300packet;

[0070] 3) w is the sampling frequency, the initial value is 160;

[0071] 4) q(k) is the instantaneou...

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Abstract

The invention discloses a method for realizing a fuzzy neuron active queue management method in IPCOP. The method comprises the following steps of: 1, defining and initializing related parameters; 2, waiting for a new data packet; 3, dynamically adjusting the neuron weighting coefficient by use of a derived Hebb learning algorithm, including the steps of sampling the instant queue length q(k) at current moment and calculating the values of the input variables x1(k), x2(k) and x3(k) of the neuron method; 4, dynamically adjusting the neuron grain K by use of a fuzzy control method, including a step of fuzzifying the input variables x1(k) and x2(k) by taking the x1(k) and x2(k) as input and the variation (delta)K of the neuron gain K as output; and 5, calculating the discard probability p(K) and discarding the data packet according to the discard probability p(k), including the steps of calculating the discard probability p(k) and finally discarding the packet according to the discard probability p(k).

Description

technical field [0001] The invention relates to a method in which a fuzzy neuron active queue management method in an actual communication network experiment platform is realized in an IPCOP software router. Background technique [0002] In recent years, computer network has been widely used as a new technology, and many researchers have done a lot of research to improve its performance. However, with the continuous development of science and technology, the scale of the network has been growing. The excessive demand for limited network resources has caused the congestion of the computer network, resulting in a large loss of network data packets, low utilization of network resources, and some other performance deterioration. . Therefore, network congestion, as a relatively serious problem, has attracted the attention of researchers. [0003] It is far from enough to rely solely on source-end control strategies and mechanisms for control. IETF (Internet Engineering Task For...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24H04L12/56
Inventor 杨晓萍陈虹郝玉香郑楠卢川宋春凤李帅刘晓娇姜健
Owner JILIN UNIV
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