## 4 Experimental Analysis
### Comparative Test and Result Analysis
RDMA communication has dramatically enhanced the I/O rate and QPS, particularly when the concurrency exceeds 200. Schemes 2 and 3 have the same I/O rate when the concurrency is less than 200, but when the concurrency is larger, the processing power of the server is fully utilized due to the process optimization of Scheme 3, and the gap between Schemes 2 and 3 is widened. At the same time, in terms of QPS, Scheme 3 also has certain advantages over Scheme 2. Figure 12 shows the comparison of the transmission performance of the traditional mode in the RDMA network in the single-client connection environment. It can be seen that the bandwidth utilization rate of the proposed model is higher than that of the traditional method in different data I/O scenarios, and the bandwidth utilization rate is increased by about 27% in the case of 4 KB data I/O. At the same time, the transmission performance  
Figure 11: Query QPS test results every second. Figure 10: I/O rate test results. significantly with a change in data volume. This shows that the reduction in the delay of each request in this model is about such an order. Similar to the previous experiment, we can conclude that the increase in transmission latency is more pronounced for small data volume I/O requests. Figure 15 shows the comparison of the bandwidth achieved by network transmission when using the model in this paper and retaining a user-mode data replication under large data volume. As can be seen from the figure, although the bandwidth peak fluctuates, the network transmission bandwidth of this model with fewer data copies is relatively higher. The reason for this is that data replication limits the performance of network transmission, and the design of this model to reduce data replication increases the bandwidth limit of network transmission. In addition, the stronger the performance of the network hardware, the greater the negative impact of the time overhead of data replication, and correspondingly, the better the optimization of data replication in this model. Figure 14: Comparison of system data transmission delay. Figure 13: Comparison of system data transmission performance under multi-client connection. (3) Client single-sided I/O effect test  
In addition to reducing data replication, another important aspect of this model for file data transfer is the Client single-sided I/O network transfer design. In this section, the read and write performances of bilateral I/O and the Client one-sided I/O modes are compared and tested in different data scale environments, and the bandwidth utilization in different environments is recorded. Figure 16 shows the performance test results of the read operation of the two network transmission models, and the performance test results of the write operation are shown in Figure 9.0  
As can be seen from the experimental results, whether reading data or writing data, the Client's single-sided I/O has improved the performance of network transmission. The Client's single-sided I/O performance improvements for read and write operations have some differences. Taking the 1 KB data volume as an example, the Client's single-sided I/O performance improvement on read operations is about 97%, while the performance improvement on write operations is about 203%. The reason for this is that in bilateral  
Figure 9.1 Comparison of client read operation performance of different network transport models. Figure 9.2 Comparison of network bandwidth for different times of data replication. I/O, after the Client completes the data write operation, the server side needs to check the integrity of the relevant data, but does not use it after reading the data. Therefore, for the Client's one-sided I/O mode, the optimization of the write data operation is relatively large. (4) Transmission delay test  
Latency is also an important indicator to measure the performance of a distributed file system.