## 5 Experimental Results and Analysis  
This chapter tests the transactions per second (TPS) and delay of the data ledger of the blockchain of the industrial Internet of Things to verify its effectiveness and feasibility. The simulation system uses Java language to simulate the 1 data generation process and 9 consensus execution process in a single machine environment. Operating environment: AMD Ryzen 7 5800H 3.20 GHz CPU, 16 GB memory, CentOS 7 operating system, JDK 1.8.0.  
(1) Throughput. TPS in the data blockchain refers to the total number of transactions that the node collects data and uploads. It sends the data summary request to the consensus confirmation and writes the ledger divided by the time. Different block generation times are taken and the test repeated 10 times in each time period; 10 times of data is shown in Figure 6, and the average value of the 10 times is taken as the TPS of the time period. The test results are shown in Figure 7. As can be seen from the figure, the transaction throughput of data blockchain is about 10,000 times/s, which can deal with most scenarios in the real industrial Internet of Things.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Kth** & **S** & **F** & **E** & **Score** & **Meaning** \\ \hline
1 & 1 & 0 & 0 & 102 & Node successfully participated \\
2 & 0 & 1 & 0 & 92 & Node failure \\
3 & 0 & 0 & 1 & 36 & Node evil \\ \hline \hline \end{tabular}
\end{table}
Table 2: Node scores.  
In order to compare the differences between the RPBFT and PBFT algorithms in TPS, the following experiments were carried out in this paper: with fixed four consensus nodes, 1000, 1500, 2000, 2500, and 3000 transactions were sent, respectively, in the same time interval. The experimental results are shown in Figure 8. The TPS of the RPBFT algorithm was significantly higher than that of the PBFT algorithm. When the transaction volume was 2500, the TPS of the RPBFT algorithm increased by about 210% compared with that of the PBFT algorithm. When the transaction volume is too large and exceeds the system's processing capacity, threads will be blocked and TPS will decline. However, on the whole, TPS of the RPBFT algorithm is still higher than that of the PBFT algorithm.  
Figure 8: Comparison of TPS under different trading volumes.  
Figure 6: Transaction throughput of different blocks.  
Figure 7: Throughput of the IIoT blockchain network.  
(2) Time delay. The delay of blockchain is the time interval between request occurrence and ledger confirmation, which consists of request broadcast transmission time, consensus algorithm execution time, and broadcast confirmation time. According to the generation time of the five blocks mentioned above, the average value of all delays is counted, and the relationship of account delay under different generation times of blocks is shown in Figure 9. In this diagram, the block generation time corresponding to the maximum TPS time delay is the ms level, which can be accepted by most IIoT application scenarios.  
In order to compare the difference between the RPBFT and PBFT algorithms in consensus delay, under the condition of four fixed consensus nodes and the same time interval, the system sent comparative experiments of 200, 400, 600, 800, and 1000 transactions, respectively. The experimental results are shown in Figure 10. In the experiment, when the transaction volume increased, the transaction delay of the PBFT algorithm grew rapidly, while the RPBFT algorithm grew slowly. When the transaction volume was 1000, the transaction delay decreased by about 50%. Therefore, when the transaction volume increases, the advantages of the RPBFT algorithm are more obvious and the delay is lower.