Estimation of Current Traffic Matrices from Long-Term Traffic Variations

Abstract

Obtaining current traffic matrices is essential to traffic engineering (TE) methods. Because it is difficult to monitor traffic matrices, several methods for estimating them from link loads have been proposed. The models used in these methods, however, are incorrect for some real networks. Thus, methods improving the accuracy of estimation by changing routes also have been proposed. However, existing methods for estimating the traffic matrix by changing routes can only capture long-term variations and cannot obtain current traffic matrices accurately. In this paper, we propose a method for estimating current traffic matrices that uses route changes introduced by a TE method. In this method, we first estimate the long-term variations of traffic by using the link loads monitored at previous times. Then, we adjust the estimated long-term variations so as to fit the current link loads. In addition, when the traffic variation trends change and the estimated long-term variations fail to match the current traffic, our method detects mismatch. Then, so as to capture the current traffic variations, the method re-estimates the long-term variations after removing monitored data corresponding to the end-to-end traffic causing the mismatches. We evaluate our method through simulation. The results show that our method can estimate current traffic matrices accurately even when some end-to-end traffic changes suddenly.