## 5 Performance Evaluation
### Performance of Optimal Network Utilization Mechanism  
We have simulated the traffic processing of the shared memory switch through the setting of the single queue of the switch in Mininet, so as to be added as the switch resource to the verification of this mechanism. Link resources are represented by bandwidth. We have implemented Sonum on ONOS controller, which is connected to the Mininet. It should be noted that the following experiments were performed at a sampling rate of 10,000:1.  
Similar to previous research [12], Sonum generates traffic using a probabilistic model, \(\text{stag}(p\), \(q)\) model, \(\text{stride}(i)\) model and random model. Sonum adopts ECMP for short flows and HSA for long flows. Both traffic models are implemented by calling iperf in Mininet. We have evaluated and compared the performance of Sonum, ECMP and Hedera [12] on standardized average bisection bandwidth and FCT.  
Figure 13 shows the overall standardized average bisection bandwidth performance of ECMP, Hedera and Sonum. In most of traffic models. Sonum has the best performance. Under the \(\text{stag}(1,0)\) model, all three schemes have achieved almost the same results. The reason is that this traffic model does not generate traffic across core and aggregation switches. Almost all of the three schemes use the ECMP method for traffic scheduling. In this model, all three schemes are equivalent to ECMP. In other words, the performance of all scheduling schemes is related to traffic models.  
In order to test the impact of different schemes on the long flow FCT, we set all the long flow sizes in the network to 100 MB, and all the short flows are set to 50 KB. Figure 14 shows the long flow FCT of three schemes. Sonum has achieved the best performance in all traffic models.  
Figure 11: Results of queue length.  
Figure 12: Queue length fluctuation (sampling rate = 1000:1).  
Figure 15 shows the improvement performance of standardized average bisection bandwidth of Sonum. Sonum increases bandwidth utilization by 18.3-36.9% compared to ECMP, and 2.1-13.5% compared with Hedera except stag(1, 0) model.  
Figure 16 shows the improvement performance of long flow FCT of Sonum. Sonum decreases FCT by 10.3-56.1% than ECMP, and 2.4-40.2% than Hedera except stag(1, 0) model.  
Figure 14: Result of long flow FCT of different load balancing schemes under different traffic models.  
Figure 13: Result of average bisection bandwidth of different load balancing schemes under different traffic models.  
Figure 15: Improvement Performance of standardized average bisection bandwidth of Sonum compared with ECMP and Hedera.  
Figure 17 shows the packet loss rate results of three schemes. In order to be convincing, we set the link loss rate in all schemes to 1%, and used iperf to record the network packet loss rate. Simulation results show that Sonum has the lowest packet loss rate. ECMP lacks congestion awareness, which may increase network congestion and further lead to network packet loss. Also, ECMP cannot avoid packet loss due to link congestion and switch congestion. Both Hedera and Sonum schedule on the long flow, which can avoid the long term occupation of network resources caused by long flow, and reduce the flow completion rate while reducing the packet loss rate. But because we use a single queue cache for the switch in Mininet, in order to simulate a shared memory switch. Hedera has packet loss due to switch congestion. So Sonum has the lowest packet loss rate. The traffic distribution of the \(\text{stag}(p,q)\) model is not concentrated, so under the stage(0.3, 0.3) and stage(0.5, 0.3) models, all three schemes perform well.