# Node Screening Method Based on Federated Learning with IoT in Opportunistic Social Networks
## 4 Results
### Experimental Results  
After the simulation parameters are determined, the simulation analysis is performed, and the analysis is completed to generate an analysis report. The degree of correlation between time and the four parameters is shown in Figures 4  
The delivery ratio and simulation time's relationship in this simulation is shown in Figure 4. The transmission rate of the traditional Spray and wait algorithm is the lowest, fluctuating between 0.32 and 0.365, because the traditional Spray and Wait algorithm is used in the transmission process in the flooding strategy. In addition, the copy ratio in its simulation is 30. Because a lot of duplicate information is copied, there will be a lot of information loss and redundancy in such a community, so the delivery is relatively low. For the SECM algorithm, it is also an algorithm based on the flooding strategy, so there is also the problem of high information loss rate, and the delivery ratio will not be very high, floating in the range of 0.36 to 0.39. The ICMT algorithm evaluates the probability of nodes, rebuilds the buffer space, controls the transmission rate of forwarded information, and makes the data transmission more stable. Therefore, the delivery is also improved compared to the previous two algorithms; it fluctuates between 0.498 and 0.568. Compared with the traditional algorithm Spray and Wait, the delivery rate has increased by about 0.36 to 0.39. The delivery ratio is about 0.49 for the 0.36 to 0. 55%. DDMPD uses a combination of multi-sensing communities and mobile nodes to increase the transmission rate in opportunistic social networks and reduce data loss, so the transmission is relatively high, fluctuating in the range of 0.55 to 0.63. The FABD algorithm is based on federated learning, because of the precise selection of nodes based on DPPO during the transmission process and the loss of the transmission process is relatively small; the delivery ratio is also better. The lowest value is 0.59, which exceeds 50%, and the highest is 0.692, The best performance among all comparison algorithms. Figure 5 shows the relationship between routing overhead and time. From the results of the simulation experiment, it can be seen that the routing overhead of the Spray and Wait algorithm is the largest among all algorithms, floating in the range of 151-297 Mb. Although the traditional algorithm is easy to understand and implement, its usability is very poor, so the routing overhead is correspondingly high. The routing cost of the SECM algorithm is between 140 and 221. Its cost is relatively stable most of the time, but there will be a certain flooding situation around 2 h. The usability is better than the traditional algorithm, but it still cannot meet the requirements. The principle of the ICMT algorithm is to select nodes based on probability evaluation, while controlling the frequency of sending information. Its maximum routing overhead appears within 2 h. It has a better control effect on overhead, and the average overhead is lower than the above two algorithms. When the DDMPD algorithm is applied to an opportunistic social network, as time increases, the number of nodes and communities participating in the propagation will increase accordingly, so the routing overhead remains relatively stable, between 105 and 116. The routing overhead of the FABD algorithm is stable and low, keeping it between 88 and 106. Because when the data transmission in the opportunistic social network adopts the FABD algorithm, the appropriate node selection will be made according to the current situation until the selected node is optimal. This will minimize the useless overhead of routing, so the algorithm performs best in controlling routing overhead. Figure 6 shows the relationship between energy consumption and time. As time increases, the increase in energy consumption of each algorithm and the trend of change are somewhat different. The energy consumption of the Spray and wait algorithm has always been the highest among all the algorithms.