TY - GEN

T1 - New methods for network traffic matrix estimation based on a probability model

AU - Tian, Hui

AU - Sang, Yingpeng

AU - Shen, Hong

PY - 2011

Y1 - 2011

N2 - Traffic matrix is of great help in many network applications. However, it is very difficult, if not intractable, to estimate the traffic matrix for a large-scale network. This is because the estimation problem from limited link measurements is highly under-constrained. We propose a simple probability model for a large-scale practical network. The probability model is then generalized to a general model by including random traffic data. Traffic matrix estimation is then conducted under these two models by two minimization methods. It is shown that the Normalized Root Mean Square Errors of these estimates under our model assumption are very small. For a large-scale network, the traffic matrix estimation methods also perform well. The comparison of two minimization methods shown in the simulation results complies with the analysis.

AB - Traffic matrix is of great help in many network applications. However, it is very difficult, if not intractable, to estimate the traffic matrix for a large-scale network. This is because the estimation problem from limited link measurements is highly under-constrained. We propose a simple probability model for a large-scale practical network. The probability model is then generalized to a general model by including random traffic data. Traffic matrix estimation is then conducted under these two models by two minimization methods. It is shown that the Normalized Root Mean Square Errors of these estimates under our model assumption are very small. For a large-scale network, the traffic matrix estimation methods also perform well. The comparison of two minimization methods shown in the simulation results complies with the analysis.

KW - NRMSE

KW - probability model

KW - traffic matrix estimation

UR - http://www.scopus.com/inward/record.url?scp=84859984732&partnerID=8YFLogxK

U2 - 10.1109/ICON.2011.6168487

DO - 10.1109/ICON.2011.6168487

M3 - Conference contribution

AN - SCOPUS:84859984732

SN - 9781457718250

T3 - ICON 2011 - 17th IEEE International Conference on Networks

SP - 270

EP - 274

BT - ICON 2011 - 17th IEEE International Conference on Networks

T2 - 17th IEEE International Conference on Networks, ICON 2011

Y2 - 14 December 2011 through 16 December 2011

ER -