## 3 Experiments and Settings
### Experimental Settings and Data Preparation  
The number of mobile nodes in our simulation is 40, and the movement area is a rectangle area of 1 km * 1 km. The nodes use the above three movement models to move, with a speed of 0-140 m/s with a 10 m/s speed interval. In order to reduce the impact of randomness on the experiment, 60 random seeds are set for each model in the same speed interval to randomize the parameters in the network, and the communication radius of the nodes varies between 150 m and 290 m. Under Ubuntu 16.04 operating system, a \"sh\" script file is written in the Bonnmotion software directory to simulate the above  
Figure 4: Framework of proposed BPNN-PP.  
motion scenario in batches. The command in.sh file: \"/home/bonnmotion-3.0.1/bin/bm -f GM_5 mSh-Str GaussMarkov -n 40 -d 500 -b -x 1000 -y 1000 -i 0 -b -g -m -h \(\$\)m -h \(\$\)n\" is used to generate the motion scenario of the Gaussian Markov model. \"-n\" represents that there are 40 nodes; \"-d\" represents that the simulation time is 500 s; \"-x, -y\" is the range setting of the simulation area; \"m\" is the lower limit of the speed interval, \"h\" is the upper limit of the speed interval, and \"rr\" is the random seed variable. Then, the generated mobility model files are converted into an NS2-usable mobility files using the command: \"/home/bonnmotion-3.0.1/bin/bmNSFile -f GM_5 mSh-Str\".  
We tested and calculated the values of the parameters varying with the communication radius in the speed range of 0-20 m/s, as shown in Table 1. Different parameters exhibit different performances at the same motion speed and R. The trend of the same parameter changing with radius R also varies across different motion models. At the same time, we store and convert all the motion processes into NS2 motion files for subsequent network performance simulation in the same motion scenario. Finally, the data of each speed and index under unique random seed and communication radius are statistically recorded.  
To evaluate the effect of mobility on the performance of network protocols, we carried out simulations in the NS2 environment [30] with the wireless ad hoc networking extension. The mobility patterns used were the same as mentioned above. The traffic pattern was generated by the Cbrgen tool of NS2. The traffic consisted of 10 constant bit rate (CBR) flows, of which the source-destination pairs were chosen at random. The data rate used was 4 packets/s, and the packet size was 64 bytes. We evaluated the performance of AODV [31] across this rich set of mobility models and observed that the mobility models might drastically affect protocol performance which will be discussed in detail in the next section. The network parameter settings are shown in Table 2 below.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Mobility** & **R** & **Spatial** & **Partitioning** & **Link** & **Relative** & **Path** \\
**Models** & & **Dependency** & **Degree** & **Duration** & **Speed** & **Availability** \\ \hline \multirow{9}{*}{GM} & 150 m & \(-\)0.015215 & 0.79171 & 12.54591 & 17.91827 & 0.215451 \\  & 170 m & \(-\)0.012723 & 0.63871 & 14.25538 & 17.92939 & 0.3729329 \\  & 190 m  
We conducted network simulation and testing using the AODV protocol as an example in the above scenario. Figure 5 displays the result of the network packet delivery ratio obtained from the testing. Among them, we set up four groups for the RPGM model, as the node contact between the groups is relatively close, the change in packet delivery rate of RPGM is relatively small as the motion speed increases, and different communication radii have a small impact on the network performance. GM and RWP's packet delivery rate decreases significantly with increasing speed and decreasing communication radius. Finally, it can be seen that the packet delivery rate performance of this routing protocol remains above 20%, so we divided the network performance levels with a 10% interval. correspond in sequence to (100%, 90%), (90%, 80%),..., (30%, 20%).