An SDN-Based Traffic Matrix Estimation Framework

Abstract

Accurate traffic matrix estimation is critical to solving many networking problems, such as routing and network provisioning, etc. This task in a traditional IP network is tackled with link load measurements. But the accuracy of such an approach is low because the underlying system of linear equations governing the traffic estimation problem is highly under-determined in this approach. A software-defined network (SDN) provides measurements of more types of flows, and thus opens up new opportunities for tackling the traffic matrix estimation problem. Furthermore, the controller of an SDN can dynamically install flows in the flow table of an SDN router for traffic measurement. But there is one constraint: the number of entries in a flow table for traffic measurement is limited because the flow table in an SDN node is usually constructed with expensive ternary content addressable memory (TCAM) devices. How to use the limited number of entries in a flow table for traffic measurement is a challenging task in SDNs. In this paper, we present a new framework for solving the traffic matrix estimation problem in an SDN-based IP network. An important feature of the proposed framework is that any flow added to the flow table of an SDN router can increase the rank of the underlying equations governing the traffic matrix estimation problem. This greatly improves the utilization efficiency of TCAM entries for traffic measurement. Detailed performance evaluation given in this paper demonstrates that the proposed approach can achieve significant performance gains over other approaches.