An estimating method for IP traffic matrix based on generalized inverse matrix

The purpose of this paper is to present research in the area of the applications of the generalized inverse matrix in IP traffic matrix.

Traffic matrices are important for many network design, engineering, and management functions. However, they are often difficult to measure directly. Because networks are dynamic, analysis tools must be adaptive and computationally lightweight. In order to manage the whole network, a novel calculating model is proposed based on the generalized inverse matrix. In this model, a generalized inverse matrix is introduced to resolve the traffic matrix equation. But if so, the error is raised. In order to improve the method, an original traffic matrix is estimated according to the prior, for example, Poisson model. To acquire the optimized solutions, linear programming is introduced. Through both theoretical analysis and simulating results, it is shown that the proposed algorithm achieves better performance than the existing representative methods.

This paper illustrates the useful information that can be obtained using generalized inverse matrix for incomplete data estimation.

The use of generalized inverse matrix was a very effective method to calculate IP traffic matrix.

The algorithms discussed in the paper can be used to estimate solutions of an ill‐posed linear inverse equation.

The paper is of value in proposing an estimation method for IP traffic matrix using generalized inverse matrix.