关键词: 软件定义网络, 负载均衡, 数据中心, 胖树拓扑

Abstract: As the amount of data increases in data center networks, the traffic load of some links is excessive. The traditional ECMP mechanism is no longer applicable to the data center network because it does not consider the link status and traffic characteristics. Meanwhile ECMP mechanism may hash some large flows to the same path. It may cause large flows collision and bring the problem of link bottleneck when scheduling flows. Based on the Software Defined Network（SDN） architecture, this paper proposes a dynamic Load Balancing scheme based on Flow Classification（LBFC） for the Fat-Tree topology, and considers link state information and traffic characteristics. LBFC mechanism dynamically adjusts the flow classification threshold to classify flows into the large and small flows. LBFC selects the forwarding path for the large and small flows in different ways to meet the different transmission bandwidth requirements of the large and small flows. The simulation results show that the LBFC can dynamically determine the large flows and small flows according to the network link status and traffic characteristics and achieve load balancing. Compared with ECMP, GFF and DLB algorithms, the LBFC mechanism improves network throughput and link utilization. The transmission delay is also reduced.

Key words: Software Defined Network（SDN）, load balancing, data center, fat-tree topology