# FlexBFT: A Flexible and Effective Optimistic Asynchronous BFT Protocol
## 5 Performance Evaluation
### Result  
In our first set of experiments, we focused on the relationship between the number of nodes and the performance of the algorithms under favorable network conditions. We set the timeout parameter to be greater than the actual network delay in the experiments and increased the number of replica nodes from 4 to 28 with a step size of 6. The experimental results are presented in Figures 3 and 4.  
The results indicate that as the number of replica nodes increases, all four algorithms exhibit significant performance scalability, each with its own emphasis on different aspects of performance. Asynchronous protocols demonstrate the ability to achieve both high throughput and low latency, even with 28 replica nodes.  
Regarding latency, HotStuff, BDT, and FlexBFT can maintain approximately 300 ms of low latency even with 28 replica nodes. In the case of BDT and FlexBFT, this is primarily due to the operation of Blot and the fast mode protocol, respectively. Their low latency is attributed to the absence of randomness, resulting in lower communication complexity. However, Dumbo, constrained by the complex MVBA, still faces a message complexity of \(n^{3}\), leading to poor latency performance, as expected. Furthermore, FlexBFT's latency is slightly lower than BDT, likely due to the separation of block download and consensus in the fast mode strategy. In terms of throughput, a situation similar to the previous case emerges, with Dumbo, HotStuff, and FlexBFT enjoying higher throughput, hovering around 10,000 transactions per second. The differences in throughput can be attributed to the AVID method used by these three protocols, which efficiently distributes the system's bandwidth load. In the case of HotStuff, where transactions are broadcasted, the main node's bandwidth becomes the bottleneck.  
Figure 3: Latency comparison.  
Figure 5 illustrates the relationship between latency and throughput under different settings (batch size). This setting introduces worse network conditions with more network fluctuations, reflecting the trade-off between latency and throughput when system bandwidth and other resources are fixed. It is worth noting that, in this scenario, a significant performance gap exists between BDT and FlexBFT. On average, for the same throughput, FlexBFT exhibits 31.6% less latency compared with BDT. This improvement is attributed to FlexBFT's strategy of back-up mode persistence, reducing the redundant fallback overhead.  
Table 1 presents an intuitive performance comparison under the same parameters (with 16 nodes and a batch size of 5000). The first two columns show data from a normal network environment, where it can be observed that FlexBFT slightly outperforms BDT. The primary comparison here is between FlexBFT's fast mode and BDT's bolt module, with the difference attributed to FlexBFT's fast mode decoupling AVID, separating consensus from block downloading, resulting in performance enhancement. The latter two columns compare  
Figure 4: Throughout comparison.  
Figure 5: Comparative throughput–latency performance.  
performance under worse network conditions, similar to what is illustrated in Figure 5, highlighting the superiority of persisting in back-up mode and the optimistic output within back-up mode.