Flow-Based Network Tomography Agent for Software Defined Data Center

In software defined networking (SDN) data centers, collecting real-time routing information of different traffic flows for tomography of data centers requires an up-to-date knowledge of every link. However, traditional techniques are mostly not covering traffic matrix (TM) estimation for specific traffic types. This paper proposes an approach to construct a tomography agent to estimate and manage traffic flows through the data center network. For this aim, we regenerated the traffic matrix according to three different traffic types (bandwidth-sensitive, delay-sensitive, best-effort) and taking into account delay information obtained from the Markov chain M/G/1 priority queuing method both for link count and traffic matrix. Consequently, after regeneration step, we use Expectation Maximization approach for iteratively estimate the traffic matrix. In addition, regarding to estimated traffic matrix, by using Max-Min fairness method and definition of flow utility function, our simulation results in reduction in end-to-end routing delay and also flow utility enhancement.