Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
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Traffic matrices constitute essential inputs in a wide variety of network planning and management functions as they provide the traffic volumes that flow between the node pairs in a network. In operational IP networks, it is desirable that traffic matrix (TM) estimation relies on information that is directly obtainable from SNMP system measurements i.e., link counts data. Existing approaches for TM estimation based on link counts have been shown to have limited accuracy and cannot be generally applied to practical IP networks. In this paper, we propose a new method for TM estimation which makes more accurate assumptions about the traffic characteristics of the flows between node pairs and, specifically, a Markovian Arrival Process of order two (MAP-2) has been applied for this purpose. The presented evaluation study shows the ability of the method to accurately capture the correlation and burstiness statistics of real IP flows and, therefore, can be successfully applied in IP network management functions.