Flat-tree
Yiting Xia, T. S. Eugene Ng · 2016
Clos networks are easy to implement, whereas random graphs have good performance. We propose flat-tree, a convertible data center network architecture, to combine the best of both worlds. Flat-tree can change the network topology dynamically, so the data center can be implemented as a Clos network and be converted to approximate random graphs of different sizes. To serve the heterogeneous workloads in data centers, flat-tree can organize the network as functionally separate zones each having a different topology. Workloads are placed into suitable zones that best optimize the performance. Simulation results demonstrate that flat-tree has similar performance to random graphs.