Network coordinate system input delay pre-treatment method based on t detection model

Abstract

The invention discloses a network coordinate system input delay pre-treatment method based on t detection model. The method is characterized in that: each network node records nearest H direct measuring delay values between the network node and partial neighbour nodes; under the t detection model, according to the delay observed value of the delay queue, confidence interval of observed value at the next moment of the node is estimated, so as to detect and inhibit abnormal delay observed value and obtain delay result smoothly output by the node. The algorithm is based on probability theory t detection model, history record delay sample information between nodes is utilized, and the abnormal delay observed value of the node at the next moment is detected and inhibited, so as to obtain delay result smoothly output by the node, the delay result is used for carrying out network distance semi measure space embedding, thus ensuring the accuracy of the node to establish network coordinate system delay system predication and convergent cycle thereof.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a method for preprocessing the input time delay of a network coordinate system based on a t-detection model. Background technique [0002] In recent years, with the exponential growth rate of the IP network scale, the heterogeneity and complexity of the network structure have increased, resulting in poor visibility of the internal performance of the network. At the same time, with the continuous emergence of new network applications, users' requirements for network service quality continue to rise. Both network service providers and users hope to have timely and accurate first-hand information reflecting the current performance of the network. Optimize network applications to the greatest extent. In the actual IP network, there are many parameters that can reflect the performance and behavior of the network, such as bandwidth, delay, throughput, etc., and the delay between ...

AI Technical Summary

Problems solved by technology

In this case, because the input of the coordinate system is a static sparse delay matrix, although the delay value between nodes is stable, it cannot dynamically reflect the congestion and topology changes in the network.

In real scenarios, whether it is network congestion, network load balancing, or network topology changes, etc., it can cause the delay value between network nodes to be unstable.

If no processing is done on the input time delays involved in the construction of the network coordinate system, the accuracy and convergence period of the time delay prediction for establishing the network coordinate system cannot be guaranteed

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