Combining LDP Measurements and Estimation Methods for Traffic Matrices in IP/MPLS Networks

In this paper we consider the problem of determining the traffic matrix of end-to-end demands in an IP network that uses multiprotocol label switching (MPLS). Although it is possible to measure end-to-end demands directly in this case using RSVP-TE tunnels it is not always desired to establish a full mesh of tunnels which is necessary to measure the complete traffic matrix: This introduces an additional routing layer and increases the operational complexity of the network. We propose in this paper a framework to generate traffic matrices by combining measurements with estimation techniques. We use statistics of the label distribution protocol (LDP) to obtain end-to-end traffic flows. These label swapping statistics can be used to calculate flows on a high aggregation level and allow for a simple and inexpensive measurement infrastructure. It depends on the network topology as well as vendor equipment what part of the traffic matrix can be determined exactly in this way. We investigate different estimation methods to complete the traffic matrix and introduce a model to additionally estimate the decomposition of the traffic matrix into traffic matrices for different QoS classes