SDN-Based Load Balancing Scheme for Fat-Tree Data Center Networks - Askar, Shavan (Al-Nahrain Journal for Engineering Sciences, 2017)
This paper proposes a new load balancing algorithm for data center networks by means of exploiting the characteristics of Software Defined Networks. Mininet was utilized as an emulation tool for the purpose of emulating and evaluating the proposed design, Miniedit was utilized as a GUI tool for the same purpose. In order to obtain a realistic environment to the data center network, Fat-Tree topology was utilized with the following parameters; 4 pods, 16 edge switches, 16 aggregation switches, 4 core switches, and 16 hosts. Different scenarios and traffic distributions were applied in order to cover as much possible cases of the real traffic. POX controller was chosen as an SDN controller.The suggested design showed outperformance when compared to the traditional scheme in term of throughput and loss rate for all the evaluated scenarios. The first scenario assumes joining of new hosts while in the second scenario; there was an increase in the demand of the already established connections. The proposed algorithm showed a loss free performance in the first scenarios, whereas, the traditional scheme presented 15% to 31% loss rate for the same scenario. In the second scenario, the proposed algorithm recorded up to 81% improvement in the loss rate when compared to the traditional scheme.  Moreover, the proposed algorithm showed a superiority over the traditional scheme in term of throughput, where it maintained the throughput intact without any reduction in the first scenario in contrast to the traditional scheme that underwent from a considerable degradation in the throughput value. The traditional scheme underwent from an average throughput reduction of 5Mbps in the case of joining of new hosts (first scenario). In the second scenario, both schemes underwent from a throughput reduction, however, the proposed scheme always showed superiority over the traditional scheme, whereas, it recorded up to 16.6% improvement in the throughput average value.