A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms

Big-data networks are raising energy use and associated ecological effects and have become a significant cause for concern in the last decade. With the expected significant increase in the traffic demand in data centres escalates the need to be energy efficient. In this scenario, the implementation of sleep mode in software defined network (SDN) data centres could provide an energy aware solution. Energy consumed of the network can be reduced by putting underutilized network devices or components to sleep. Employing sleep mode aligns with sustainability goals and can reduce the environmental impact of data centers by lowering carbon emissions. In this work meta heuristic algorithm is incorporated at the SDN central controller in a fat tree-based data centre for bandwidth usage monitoring, sleep decisions and path selection using Mininet emulation. The Mininet emulation performance study was conducted based on comparison between metaheuristic and Dijkstra method. The proposed sleep mode method obtained enhancement in the performance parameter with uses less energy in the network.