Traffic matrix estimation enhanced by SDNs nodes in real network topology

Traffic matrix estimation in communication networks is challenging problem, whose solution provides a valuable management and planning tool. Given the range of technologies able to reconfigure the resource assignment, real-time knowledge of the traffic matrix enables smart adaptive traffic management functions. A new perspective is given to the traffic matrix estimation problem by the Software Defined Network (SDN) concept. We investigate an evolutionary approach, where SDN nodes are introduced into a traditional IP network, to understand how their new capabilities affect the statement and accuracy of the traffic matrix estimation problem. By referring to operational networks and benchmark measured data, we show that a major boost of estimate accuracy can be obtained with very few SDN nodes, performing very simple tasks. To that end we develop an underlying theory that helps locating SDN functionalities in the most convenient way.