A Link Load Balancing Algorithm Based on Ant Colony Optimization in Data Center Network

With the continuous increase of types of services and data volume in data center, the traffic loads of some links are excessive, and how to balance the link load and ensure the quality of network service have become research hotpots. However, the traditional link load balancing mechanisms ignore the complexity of network and the Quality of Service (QoS) requirement of the flow when calculating the forwarding paths. Therefore, we propose a link load balancing algorithm based on Ant Colony Optimization (LLBA) in data center network. The algorithm redefines the heuristic function according to the number of elephant flows on the link and the real-time load of links, and updates the pheromones according to the path length. Then, the algorithm customizes the optimal path determination rule according to the path transmission delay and the real-time loads, so as to find a best forwarding path for the current flow under the multiple constraints including the path length, link load, and transmission delay. The experiment results show that, the proposed algorithm improves the link utilization and network throughput effectively, and also reduces the delay and delay jitter to some extent, as compared with the traditional mechanisms.