Traffic Engineering in Cloud Data Centers: A Column Generation Approach

While many have advocated for the use of Virtual Local Area Networks (VLANs) as a way to provide scalable traffic management, finding the optimal traffic split (mapping) among VLANs to achieve load balancing has turned out to be a very challenging and combinatorially complex problem to solve. This paper considers the traffic engineering problem in data center networks by studying the joint problem of finding spanning trees for VLANs and optimally selecting the most promising spanning trees to map the traffic flows onto. We mathematically model this problem using Integer Linear Program (ILP) techniques and follow a primal-dual decomposition approach, using column generation, to solve exactly a relaxed mapping version of the problem, as well we present approximate solutions to the original problem. We show through numerical evaluations an outstanding scalability of the decomposed version of the problem and we use our results to study the performance of traffic engineering protocols developed in recent literature for data center networks.