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

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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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 algorithm according to the network load status, so that the AQM The system adaptively adjusts its own parameters to improve control performance. This system solves the problem that the parameters of the RED algorithm cannot be set in real time, and the change of network load easily causes the instability of the AQM system.

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