RED-based network congestion control algorithm

Abstract

The invention discloses an RED-based network congestion control method. The algorithm comprises the following steps of: segmentally processing different congestion states by introducing a fifth-order classification method in the statistics, dividing the network congestion states by using five indexes of weak, slight, medium, serious and severe, and dividing the average queue utilization rate into five regions, each of which corresponds to a network congestion state; calculating the discard probability of the average data size of the regions by utilizing a liner function of a data size distribution probability; and discarding data packets in corresponding regions in the probability according to the current congestion state to increase the available space of queues so as to avoid the network congestion. In the algorithm, original ten configuration parameter projects of the conventional algorithm are reduced to two, so that the configuration difficulty is obviously reduced. Under the same network scene, the average queue cache utilization rate is about 25 percent higher than that of an RED derivative algorithm. The algorithm improves the network congestion control effect, can flexibly adjust the packet loss number according to the congestion degree, and effectively inhibit network jitter.

Description

technical field [0001] The invention belongs to the technical field of computer network management, and relates to a network congestion control method in network quality of service (QoS: Quality of Service) management, in particular to a network congestion control method based on random early detection RED. Background technique [0002] In 1988, American scientist Van Jacobson and others discovered that network congestion is caused by links or network nodes carrying excessive data, and the queue buffer of network nodes is full, resulting in a large amount of data being discarded and service response delays increasing. As the scale of network applications continues to expand, the demand for network bandwidth resources continues to rise, and network congestion occurs frequently under limited bandwidth capacity. Network congestion control has become a key factor in improving network service quality. For the case of not changing the physical structure of the network, how to maxi...

AI Technical Summary

Problems solved by technology

Passive queue management is a type of queue truncation (Droptail) management, that is, the network data fills the queue buffer and then discards the data packets that arrive one after another. It has three main defects: (1) The queue is full, and the queue is forced to be dropped after the queue is full. packets, other data cannot enter the queue; (2) deadlock, high burst traffic occupies all queue buffers instantaneously, and other types of data cannot pass through; (3) TCP global synchronization, when the queue discards multiple TCP data packets at the same time, each TCP synchronization reduces message sending, and network throughput drops sharply

However, according to the research of American expert Feng W et al., network congestion control not only depends on the statistical characteristics of the average queue length, but also depends on the distribution of network data arrival time interval and data size distribution. Effectively solve the problem of network congestion control, but also easily cause network jitter, resulting in a decrease in network utilization

In addition, RED and related improved algorithms need to set more than 10 parameters such as average queue size, packet loss probability, upper and lower thresholds of queue packet loss, average data packet size, average network transmission rate, average network transmission delay, and burst volume of data transmission. , and there is no clear rule limit and theoretical basis for the parameter setting, it is mainly set by the experience of the network administrator, and the parameter value has a great influence on the operation effect of the congestion control algorithm

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