The software-defined networks (SDN) not only enable the control plane to be coupled with the data plane, further can be also used to optimize the aviation swarm network architecture. In view of satisfying the demand of large-scale aviation swarm networking, a controller deployment optimization algorithm for large-scale aviation swarm networks (ASNs) is designed. The proposed algorithm transforms the deployment of multiple controllers into two phases, i.e., the swarm division and sub-swarm deployment. First, the swarm is divided into sub-swarms according to the load balance, and then the multiple-objectives optimization is performed in each sub-swarm based on the global optimum to obtain the Pareto frontier solutions. The simulation experiment evaluates the performance of the proposed algorithm in terms of the load balance index, average propagation delay and average disconnection probability of the entire network. The experimental result shows that compared with the existing algorithms, the proposed algorithm effectively enhances the performance of the entire network, and has lower time complexity. And the proposed algorithm is available for addressing the controller deployment issue in large-scale and dynamic ASNs.