## 3 An Opportunistic Routing for Data Forwarding Based on Vehicle Mobility Association
### Node Traversal Process  
As shown in Figure 3, let the \(v_{1}\) be the source node which needs to send some messages to the destination node \(v_{45}\). The implementation process of the algorithm based on Figure 2 is as follows:  
At the initial state, all adjacent nodes are associated with equal degrees (\(\delta_{ij}(t)\) = Q). Step 1. Accessing neighboring nodes of the \(v_{1}\) and calculating the data transfer probability. All nodes with a transition probability greater than \(\tau\) (\(p_{v_{1},v_{1}}(t)>\tau\)) are used as the next access node (\(v_{1}\to v_{2}\), \(v_{1}\to v_{11}\), \(v_{1}\to v_{16}\), \(v_{1}\to v_{12}\), \(v_{1}\to v_{36}\)), and these nodes are recorded in the _tabu_ table (\(v_{2}\), \(v_{11}\), \(v_{16}\), \(v_{12}\), \(v_{36}\in tabu_{n}\)). Step 2. Accessing adjacent nodes of \(v_{2}\), \(v_{11}\), \(v_{16}\), \(v_{12}\), \(v_{36}\) and calculating the data transfer probability. All nodes with a transition probability greater than \(\tau\) (\(p_{v_{2},11,1612,36,v_{1}}(t)>\tau\)) are used as the next access  
Figure 2: The difference between Euclidean distance and cosine similarity. node (\(v_{2}\to v_{9}\), \(v_{16}\to v_{3}\), \(v_{12}\to v_{3}\), \(v_{12}\to v_{10}\), \(v_{36}\to v_{5}\)), and the resulting nodes are recorded in the _tabu_ table (\(v_{9}\), \(v_{3}\), \(v_{10}\), \(v_{5}\in tabu_{n}\)). Step 3. Accessing adjacent nodes of \(v_{9}\), \(v_{3}\), \(v_{10}\), \(v_{5}\) by calculating the data transfer probability, finding all the nodes with a transition probability greater than \(\tau\) (\(p_{v_{3},13,05,v_{2}}(t)>\tau\)) as the next node (\(v_{9}\to v_{7}\), \(v_{9}\to v_{13}\), \(v_{3}\to v_{14}\), \(v_{3}\to v_{23}\), \(v_{5}\to v_{34}\)), and the resulting nodes are recorded in the _tabu_ table (\(v_{7}\), \(v_{13}\), \(v_{14}\), \(v_{23}\), \(v_{34}\in tabu_{n}\)). Step 4. Accessing adjacent nodes of \(v_{7}\), \(v_{13}\), \(v_{14}\), \(v_{23}\), \(v_{34}\) by calculating the data transfer probability, finding all the nodes with a transition probability greater than \(\tau\) (\(p_{v_{7},13,14,23,34,v_{2}}(t)>\tau\)) as the next node (\(v_{14}\to v_{23}\), \(v_{14}\to v_{29}\)), and the resulting nodes are recorded in the _tabu_ table (\(v_{29}\in tabu_{n}\)). Because the \(v_{23}\) node as the subsequent node \(v_{3}\) has passed the message, \(v_{23}\) has been accounted for in the tabu list. It will not be used to deliver the message again. Thus, the \(v_{14}\) node in the \(v_{23}\) node path will not deliver the message. Step 5. Accessing adjacent nodes of \(v_{29}\) by calculating the data transfer probability, finding all the nodes with a transition probability greater than \(\tau\) (\(p_{v_{29},v_{1}}(t)>\tau\)) as the next node (\(v_{29}\to v_{37}\), \(v_{29}\to v_{39}\)), and the resulting nodes are recorded in the _tabu_ table (\(v_{37}\), \(v_{39}\in tabu_{n}\)). Step 6. Accessing adjacent nodes of \(v_{39}\), \(v_{39}\) by calculating the data transfer probability, finding all the nodes with a transition probability greater than \(\tau\) (\(p_{v_{39},v_{37},v_{1}}(t)>\tau\)) as the next node (\(v_{39}\to v_{45}\)), and the resulting nodes are recorded in the _tabu_ table (\(v_{45}\in tabu_{n}\)). Step 7. A set of the maximum data transfer probability nodes is found as the best path for this message, and the path is recorded in the Er table (\(v_{1}\)-\(v_{12}\)-\(v_{3}\)-\(v_{14}\)-\(v_{29}\)-\(v_{39}\)-\(v_{45}\)). If a node data transfer probability greater than \(\tau\) cannot be found, reduce the value of the data transfer probability (\(p_{i,j}(t)>\varsigma\)). Repeating these steps until a path with the largest data transfer probability is identified as transmitting this message. Step 8. Computing adjacent node affinity for optimal path obtained (\(\delta_{ij}(t)=1-\tilde{\varsigma}_{ij}(t)\)), and the result is saved in Ec table. If the Ert is sufficient, is still delivers messages in accordance with the above procedure.