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In order to solve the increasingly serious network congestion, a node closed loop PID control mechanism is proposed, which is based on BP neural network (abbr. BPNN). This mechanism works with active queue management (abbr. AQM) scheme with probability drop strategy, which forms a closed loop by controlling node buffer average queue size. The method tries to avoid the disadvantages of the traditional...
The paper designs a new AQM algorithm called ANPID, which applies the theory of adaptive linear neuron to AQM controller in congestion control. ANPID can adjust the queue length to the desired value, revise its weights online by LMS learning rule, and tune the coefficients of PID controller. The weighted factors are regulated continuously according to the system errors, as well as eliminate the sensitivity...
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