## 3 SDVN Traffic Analysis and Prediction  
The collected traffic information is summarized and analyzed. Some data flow information is shown in Table 2:  
As shown in Table 2, the table has eight fields, namely 'number', 'number of packets', 'packet size','source address', 'target address','switch number', 'traffic size', and 'controller'. Taking the 0 th datapoint as an example, the number of data packets in the data stream is 1, the size of the data packet is 42 Bytes, the source address is 10.1.1.2, the target address is 10.1.1.6, the switch number used is 1, the traffic size is 'low', and the connected controller RSU is A. The number of data streams flowing through the four controllers A, B, C, and D is 240, 166, 213, and 220, respectively; after statistical summary analysis, the flow size and proportion of different controllers are shown in Table 3, where 0 indicates 'low' and 1 indicates 'high'. As shown in Table 3, the proportion of high and low flow through A controller is 50.00% and 50.00%, respectively. The proportion of high and low flow through B controller is 45.18% and 54.82%, respectively. The proportion of high and low flow through C controller is 38.03% and 61.97%, respectively. The proportion of high and low flow through the D controller is 31.82% and 68.18%, respectively. The number of 'high' and 'low' data streams flowing through each controller is shown in the fourth column. The traffic information provided by taxis equipped with GPS equipment (or online ride-hailing) is summarized, and the total number of data streams flowing through the four controller RSUs is 839. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**ID** & **Packet Number** & **Packet Size** & **Switch Number** & **Traffic** & **Controller** & **Source Address** & **Destination Address** \\ \hline
1 & 1 & 42 Bytes & 1 & Low & A & 10.1.1.6 & 10.1.1.2 \\
2 & 2 & 84 Bytes & 1 & Low & A & 10.1.1.6 & 10.1.1.2 \\
3 & 20 & 1960 Bytes & 1 & High & A & 10.1.1.2 & 10.1.1.6 \\
4 & 20 & 1960 Bytes & 1 & High & A & 10.1.1.6 & 10.1.1.2 \\
5 & 2 & 84 Bytes & 1 & Low & A & 10.1.1.2 & 10.1.1.6 \\
6 & 1 & 42 Bytes & 1 & Low & A & 10.1.1.3 & 10.1.1.7 \\
7 & 20 & 1960 Bytes & 1 & High & A & 10.1.1.7 & 10.1.1.3 \\ \hline \end{tabular}
\end{table} 
Table 2: Data flow. The purpose of placing controllers is to minimize the number of controllers required to cover a given network map while placing them at RSUs with significant locations. On the other hand, it is also necessary to allocate workloads fairly between controllers. The data set is divided into a training set and a test set, with 639 training sets and 200 test sets. The process of creating a training set and a test set is as follows. Corresponding to the four controllers A, B, C, and D, 839 network traffic datapoints of the overall data set are randomly sampled. Each controller obtains 50 instances, making a total of 200 pieces of network traffic information; the remaining 639 pieces of network traffic information form the training set. The ratio of large and small traffic corresponding to the 50 pieces of network traffic information of the four controllers A, B, C and D in the test set after sampling is shown in Table 4:  
As shown in Table 4, for the flow size column, the value '0' means 'low' and '1' means 'high'. The flow composition flowing through A controller is 'high':'low' = 50.00%:50.00%; the flow composition of B controller is 'high':'low' = 32.00%:68.00%; the flow composition of C controller is 'high':'low' = 38.00%:62.00%; and the flow composition of D controller is 'high':'low' = 44.00%:56.00%. In order to predict the size of network traffic, the data set is divided into a training set and test set, of which the training set contains 639 data and the test set 200. At the same time, the training set is further divided: 511 data are used for training, and 128 data are used for verification. Since the traffic is classified by size, the subsequent traffic prediction problem is a binary classification problem.