Network traffic estimation method

Abstract

The invention discloses a network traffic estimation method which comprises the following steps of: acquiring a routing matrix and a link load; removing one part of load occupied by known origin destination (OD) pair traffic in the acquired link load, and marking unknown OD pair traffic through a master network node and the OD pair of the known traffic; estimating the acquired unknown OD pair traffic by utilizing a linear programming (LP) algorithm; reconstructing the total OD by using the known OD pair traffic and the estimated OD pair traffic; interpolating the acquired unknown OD pair traffic based on kernel principal component analysis (KPCA) cluster; and correcting the OD pair traffic estimated by the LP by using the interpolated OD pair traffic to obtain the optimal solution. According to the method, the IP network traffic matrix is accurately estimated under the condition that the partial OD pair traffic is known, the lost OD pair is interpolated by employing the KPCA, the computation complexity is reduced, and the method can be used for processing a large-scale traffic matrix (TM).

Description

technical field [0001] The invention belongs to the technical field of computer network communication, and particularly relates to a method for estimating network traffic therein. Background technique [0002] With the rapid development of Internet technology, the diversification of network types, large scale, and complex structure have become a trend, and the changes of various performance parameters in the network are becoming more and more complicated. The measurement of various performance parameters in communication networks is the basic research content of network behavior, and it is also the basis of network optimization design and management, network monitoring and evaluation, traffic anomaly monitoring and analysis, etc. In order to better design, monitor, and manage the network, it is necessary to understand and perceive the dynamic changes of these network status parameters, including parameters such as link delay, network topology, and network OD-to-traffic. By ...

AI Technical Summary

Problems solved by technology

In the estimation of the actual traffic matrix, since there are many network nodes to be estimated and the time points are relatively long, the TM is very large. If the dimensionality reduction calculation is not performed, the calculation will be very large and the calculation is very complicated, and the environment configuration for the calculation is required. High expectations

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