# A Placement Method of the 5G Edge Nodes Based on the Hotspot Distribution of Mobile Users
## 4 Our Experiments
### The Location Selection Experiment of Base Station Placement  
Our experiments test the high load utilization rate of the base station and the bandwidth reduction rate of a core network using different methods. Some baseline methods [19; 20] for comparison include:  
1. Top-U. This method [20] takes the hotspots with the Top \(N\) number of users as candidate locations of base stations. In this strategy, more users mean more data  
Figure 5: The hotspot extraction experiments at different \(P_{t}\).  
Figure 6: The hotspot extraction experiment at different \(T_{d}\).  
traffic in the base station. So, the bandwidth savings on the core network are the greatest when these candidate locations are plcaed the 5G edge nodes.
2. Top-T. In this method [20], the hotspots with the Top \(N\) duration time are used as candidate locations of base stations. The longer the duration of the hotspot, the more it means that this hotspot will be in a state of high demand for a long time, so the higher the utilization rate of edge nodes deployed in 5G base stations can be obtained.
3. Random. This method randomly selects \(N\) hotspots in the candidate hotspots to deploy the 5G base stations.  
We cluster our experimental dataset with _Eps_ = 0.002 and _MinPts_ = 400 and extract some hotspots from these clusters using \(S_{t}=2\), \(P_{t}=1\), and \(T_{d}=2\). Based on these hotspots, we test the high load utilization rate and the bandwidth reduction rate under four strategies.  
Figure 6(a) shows the effect of the number of 5G edge nodes deployed on the high load utilization rate of base stations. As we can see from this figure when the number of edge nodes deployed is the same, Top-T has the highest utilization rate of base stations in high load, followed by our method (here, \(\alpha=\beta=0.5\)), Top-U ranks third, and random method has the lowest. When \(\alpha=1\), our method is equivalent to Top-T. Further tests show that when the number of deployed edge nodes is the same, compared with Top-U, the high load utilization rate of our method can be increased by up to 7.69%.  
Figure 6(b) shows the effect of the number of edge nodes deployed on the bandwidth reduction rate of the core network. As we can see from Figure 6(a) when the same number of edge nodes are deployed, the core network bandwidth reduction rate of Top-U is the highest; our method is the second highest (here, the weight parameter is set to \(\alpha=\beta=0.5\)), Top-T is the third, and random method is the lowest. When \(\beta=1\), our method is equivalent to Top-U. Compared with the Top-T, the bandwidth reduction rate of the core network in our method can be improved up to 6.34%.  
In addition, through further analysis of two experiments, we can see that with the increase of the number of edge nodes, the high load utilization rate and bandwidth reduction rate both increase rapidly at the beginning, but when the number of of 5G edge nodes deployed reaches about 80% of the number of candidate base stations, the growth rates of bandwidth reduction rate has been decreased. Obviously, the benefits of deploying the same number of 5G edge nodes at this time are decreasing.  
Figure 7(a) shows the clustering results of our reconstructed experimental data based on DBSCAN with _Eps_ = 0.002 and _MinPts_ = 400. Figure 7(b) shows the center coordinates of hotspot areas extracted from the clustering results. These coordinates will eventually be used as candidate locations for deploying 5G edge nodes.  
Figure 6: Experiments of high load utilization rate and bandwidth reduction rate.  
In Figure 7(a), the dark blue lines are the trajectory formed by the user's locations, and the colored dots are the clustering centers. In Figure 7(b), the green lines are the user's trajectory, and the blue dots are the center coordinates of hotspot areas extracted from clusters.