## 5 Results
### Message Reliability and Net Reliability Analysis  
In the proposed system, by increasing number of the exchanged messages, message reliability increases. Figure 6 indicates message reliability for three types of the events over time in the simulated environment for a given vehicle. As illustrated in Figure 6, by forwarding messages, their reliability increase. However, may exist several vehicles that do not forward event messages, hence the convergence speed of the message reliability reduce or fix (see Figure 6c Epoch 3000-17,000). Furthermore, if vehicles send fake messages, the message reliability can decrease (see Figure 6b Epoch 13,000). Figure 6: Changes of message reliability over time. (**a**) Event 1 (i.e., Accident); (**b**) Event 2 (i.e., Traffic); (**c**) Event 3 (i.e., Road Destruction). Like as message reliability, the net reliability calculated by RSUs converges. This convergence has been shown in Figure 7 for three event messages originated from given vehicles. As shown in this figure, the net reliability increases over time. In the above simulations, it is assumed that the event rates of accident, traffic, and road destruction are \(\frac{2}{\xi}\), \(\frac{2}{\xi}\), and \(\frac{1}{\xi}\), respectively. In this subsection, it is shown the effect of event rates on message reliability and net reliability and their convergences. The event rates \(P(m)\) had been employed in Equations (2) and (3). As shown in Figure 8 by increasing the event rate, net reliability for a message originated from a given vehicle is reduced. Another criterion that may have a significant effect on the message and net reliability, and also on the performance of the system, is the radius that a vehicle is able to send or receive a message. As illustrated in Figure 9, increasing the vehicle's radius increases the message and net reliability. Growing the radius increases the number of vehicles that receive or send a given message, thus message and net reliability increase. Number of vehicles is another determinant parameter. As the number of vehicles increases, a specific event message may be sent over and over again, which results in increasing message and net reliability. Furthermore, in this situation, fake messages have less impact on the reliability. Figure 10 shows reliability changes over different number of vehicles. Number of blocks in the Blockchain and required time to mine a new block are important factors in the performance of the system. These factors depend on the number of times the messages are forwarded in the network. Figure 11 indicates the effect of number of messages in the network on number of blocks in the Blockchain and required time to mine. The sharding consensus algorithm in the proposed system scales up the performance nearly linearly with the computational power of RSUs. It provides promising scalability in the simulation. To assess accuracy and precision of the proposed system, it is considered as a classification system in which any vehicle can classify the received message into two classes, correct and incorrect. In this way, it is defined: True positive (_TP_): If a received correct message is classified as a correct message by a vehicle; True negative (_TN_): If a received incorrect message is classified as an incorrect message by a vehicle; False positive (_FP_): If a received incorrect message is classified as a correct message by a vehicle; False  
Figure 7: event OS value evaluation. (**a**) Event 1 (i.e., Accident); (**b**) Event 2 (i.e., Traffic); (**c**) Event 3 (i.e., Road Destruction). negative (_FN_): If a received correct message is classified as an incorrect message by a vehicle. Therefore, precision and accuracy of the system are given by  
\[Precision=\frac{TP}{Tp+FP} \tag{13}\]  
\[Accuracy=\frac{TP+TN}{Tp+FP+TN+FN} \tag{14}\]  
Figure 8: Message reliability values for different event rates. (**a**) Accident event; (**b**) Traffic event; (**c**) Road destruction event.