Adaptive congestion control method for communication network

Abstract

The invention relates to an adaptive congestion control method for a communication network and belongs to the technical field of network engineering. The method comprises the following steps: calculating a queue difference e(k) in each sampling period; measuring input flow rate r(k) of a data package; calculating a data flow rate difference x(k); calculating a variance ratio deltar(k) of the dataflow rate; obtaining an average value delta*(k) of the variance ratio of the data flow rate; comparing a transient queue error e(k) with a preset error threshold e[th]; calculating a modified price pr(k) and probability conversion coefficient mu(k) according to a selected control method; calculating a drop probability p(k) by the following formula according to the price pr(k) and the conversion coefficient mu(k), and performing data package drop operation. The method requires simple structure and has strong expandability, and can effectively solve technical problems in REM, reduces route queuing time delay and jitter, ensures high link availability, and has good adaptability in a complicated dynamic environment.

Description

technical field [0001] The invention relates to a control method in the technical field of network engineering, in particular to a communication network adaptive congestion control method. Background technique [0002] With the rapid development of computer network and communication technology, the number of users has increased sharply, and a large number of new services and applications have emerged continuously, which has led to more and more serious network congestion problems. The occurrence of congestion will lead to a serious decline in network performance, such as: an increase in the loss rate of data packets, an increase in network transmission delay, and a decrease in link utilization. The researchers found that simply increasing network resources cannot solve the problem of network congestion. Therefore, congestion avoidance and control techniques must be equipped in the network. [0003] At present, there are mainly two methods to implement network congestion co...

AI Technical Summary

Problems solved by technology

Among them, BLUE, AVQ, and GREEN follow the heuristic design rules, parameter configuration is difficult, and it is impossible to achieve a compromise between low transmission delay and high link utilization, and poor environmental adaptability and robustness

PI and PID are designed using the method of control theory. Although some shortcomings of RED have been overcome, there are still many shortcomings, mainly: poor queue responsiveness, queue overshoot often occurs in a dynamic network environment, and even cause queue overflow or emptying ; In addition, the parameters of PI and PID are fixed, and are only obtained by trial and error, without reliable scientific basis, which is also the main reason for their poor environmental adaptability

REM uses the concept of "price" in the network traffic optimization theory proposed by Kelly to detect and control the congestion state of the network. It has a certain application prospect, but the following problems greatly limit its application and promotion. : 1) The price of REM has insufficient ability to detect congestion, and the queue response is poor; 2) Network performance is sensitive to REM parameters; 3) REM has poor environmental adaptability, and it is difficult to ensure good performance in complex and changeable actual networks

[0006] After searching the prior art documents, no reports of technical documents related to the subject of the present invention have been found

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