In this paper we present OpenTM, a traffic matrix estimation system for OpenFlow networks. OpenTM uses built-in features provided in OpenFlow switches to directly and accurately measure the traffic matrix with a low overhead. Additionally, OpenTM uses the routing information learned from the OpenFlow controller to intelligently choose the switches from which to obtain flow statistics, thus reducing the load on switching elements. We explore several algorithms for choosing which switches to query, and demonstrate that there is a trade-off between accuracy of measurements, and the worst case maximum load on individual switches, i.e., the perfect load balancing scheme sometimes results in the worst estimate, and the best estimation can lead to worst case load distribution among switches. We show that a non-uniform distribution querying strategy that tends to query switches closer to the destination with a higher probability has a better performance compared to the uniform schemes. Our test-bed experiments show that for a stationary traffic matrix OpenTM normally converges within ten queries which is considerably faster than existing traffic matrix estimation techniques for traditional IP networks.
['Amin Tootoonchian', 'Monia Ghobadi', 'Yashar Ganjali']
OpenTM: traffic matrix estimator for OpenFlow networks