Abstract: Aiming at the problem of unreasonable traffic-path allocation and elephant flow collision in data center networks, we proposed a 
software defined network (SDN) flow scheduling algorithm based on discrete partical swarm optimization. The algorithm redefined the search  process within the partical swarm with the goal of optimizing  network performance,  dynamically allocated optimal paths for  data center traffic to reduce elephant flow collision, and introduced Metropolis to design  diversified optimal  scheduling scheme to ensure reasonable scheduling of data center traffic. The experimental results of  comparing and verifying with other flow scheduling algorithms show that the algorithm improves network quality, reduces  elephant flow delay, and achieves a better
 load balancing of network.

Key words: data center, software defined network (SDN), discrete particle swarm optimization, flow scheduling, load balancing