The Load Balancing Research of SDN based on Ant Colony Algorithm with Job Classification
WuCai Lin, LiChen Zhang · 2016
In this paper, we propose a dynamic load balancing algorithm conbined with job classification and ant colony algorithm in SDN network cloud computing environments.After scene analysis was done, we classify the server nodes that have the same processing capability of the CPU into a small cluster sub-network in SDN with the classify SDN network server nodes.With the help of SDN control plane and forwarding layer separation characteristics, we create a central controller whose work is to monitor the entire network the network, and there is a sub-controller int each sub-network.Ant colony algorithm runs in each controller.When a job comes, the central controller first finds the corresponding sub-network based on the job demand for CPU performance and send the job to the sub-network controller,then in the sub-network, the ant colony algorithm can calculate the minimum load Link Road with the real-time network load provide by the controller.In the end,the controller send forwarding policy to the switch.We build the SDN environment with the Mininet and OpenDayLight controllers, and through the algorithm experiment with other load-balancing algorithm ,the experimental results proves: the optimized ant colony algorithm can achieve better load balancing in each link which results in improving the utilization of resources and enhancing the usability of the system.