AQM (Active Queue Management) system and method based on generalized PID (Proportion Integration Differentiation) random early detection algorithm

A random early detection, generalized technology, applied in the transmission system, digital transmission system, electrical components, etc., can solve the problems of AQM system instability, RED algorithm parameters cannot be set in real time, etc., and achieve high throughput effect

Active Publication Date: 2015-04-01
南京华睿智光信息科技研究院有限公司
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Problems solved by technology

[0003] The purpose of the present invention is to provide an AQM system based on a generalized PID random early detection algorithm. The system combines the BP neural network and utilizes the generalized PID controller in the control theory to dynamically adjust the maximum discarding probability of the RED algorith

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  • AQM (Active Queue Management) system and method based on generalized PID (Proportion Integration Differentiation) random early detection algorithm
  • AQM (Active Queue Management) system and method based on generalized PID (Proportion Integration Differentiation) random early detection algorithm
  • AQM (Active Queue Management) system and method based on generalized PID (Proportion Integration Differentiation) random early detection algorithm

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[0033] The invention will be further described below in conjunction with the accompanying drawings of the description.

[0034] Such as figure 1 As shown, a flow chart of AQM system based on generalized PID random early detection algorithm, the implementation process of the system is designed, the system includes BP neural network module, generalized PID controller module, random early detection algorithm module.

[0035] The functions of the BP neural network module are: First, it can highly approximate the nonlinear mapping of any two different dimensional spaces. If the number of input units of the neural network is m and the number of output elements is n, then in the m-dimensional Euclidean space There is a bounded subset A, and there is a mapping to a bounded subset F(A) of n-dimensional Euclidean space; secondly, the neural network has the function of self-learning, and it passes the input layer, hidden layer, output The mutual weight connection between layers dynamica...

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Abstract

The invention discloses an AQM (Active Queue Management) system and an AQM method based on a generalized PID (Proportion Integration Differentiation) random early detection algorithm. The system comprises a BP neural network module, a generalized PID control module and a random early detection module, wherein the BP neural network can be used for finding out parameters under a certain optimal control law by self learning; the generalized PID control module is used for performing proportion, integration and differentiation operations on regulated own parameters and stabilizing the queue length under different network loads at a corresponding fixed value; the random early detection module is used for acquiring the fixed value as a maximum dropping probability and generating a dropping probability suitable for a current load by self-regulation; a controlled object gives a corresponding response according to the dropping probability, so that the queue length in a router can be stabilized at an expected value. Therefore, the utilization rate of network resources is increased and the average time delay of a network can be reduced.

Description

technical field [0001] The invention relates to an AQM system, in particular to an AQM system based on a generalized PID random early detection algorithm. Background technique [0002] An important goal of Active Queue Management (ie: AQM) is to detect network congestion early and send instructions to the system to control congestion, so that the queue length in the router can be stabilized to an expected value. This stability can improve the utilization rate of network resources and reduce the average network delay. The main algorithm of AQM, the random early detection algorithm, has been widely used in IP and asynchronous transfer mode (ie: ATM) routers, and has achieved certain results. However, since the parameter setting of the random early detection algorithm (ie: RED algorithm) has not been well resolved, the change of the network load is likely to cause the instability of the AQM system, so its performance has been greatly affected. From the perspective of RED's wo...

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Application Information

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IPC IPC(8): H04L12/863H04L12/865H04L47/6275
Inventor 秦立庆周井泉
Owner 南京华睿智光信息科技研究院有限公司
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