## 8 Simulation and Results
### Results
Figures 10-13 present the resource utilization performance at different numbers of deployed vehicles, with the specifications introduced in Table 7. For tasks of Category (I), i.e., results introduced in Figure 10, the traditional VANET and traditional MEC-VANET provide efficient resources; however, the proposed system offers computing resources with capabilities higher than the system requires. This reduces the utilization efficiency in this case and for the Category (II) tasks introduced in Figure 11. For tasks of Categories (III and IV), the proposed system achieved higher utilization efficiency than other simulated systems, mainly for larger numbers of deployed vehicles. This can be interpreted in the same way as for Figures 8 and 9. Similarly, Figures 14-17 provide the obtained results of the resource utilization of the four simulated systems at different traffic densities for the specifications introduced in Table 8.  
Figure 11: Average resource utilization efficiency at different numbers of vehicles for Category (II) tasks. Figure 12: Average resource utilization efficiency at different numbers of vehicles for Category (III) tasks. Figure 4:0 Average resource utilization efficiency at different numbers of vehicles for Category (I) tasks. Figure 4:1 Average resource utilization efficiency at different TDs for Category (I) tasks. Figure 4:2 Average resource utilization efficiency at different numbers of vehicles for Category (IV) tasks. Figure 4:3 Average resource utilization efficiency at different TDs for Category (II) tasks. To evaluate the availability of the proposed microservice-based VANET, the average number of the blocked tasks, i.e., tasks that cannot be handled during simulation due to unavailability of resources or other reasons, was measured. The developed and existing systems used for comparison were simulated with Categories (III and IV) tasks. We considered these categories and neglected the first two categories since these tasks have constraints regarding QoS time. Tasks of the first two categories require low computing resources and have little constraints in terms of QoS time. Figures 18-23 present the average percentage of BT (%BT) compared to the total number of assigned tasks during the simulation. Figures 18 and 19 present the average %BT at different vehicle mobilities for the specifications introduced in Figure 4:4 The proposed model outperformed the existing systems for the two categories of applications. This is due to the introduction of microservices and the increase of available resources introduced by fog nodes. Moreover, the system achieved higher performance at higher mobilities due to the proposed migration scheme with the microservice approach. Figure 4:5 Average resource utilization efficiency at different TDs for Category (III) tasks. Figure 4:6 Average resource utilization efficiency at different TDs for Category (IV) tasks. Figure 4:7 %BTs at different vehicle mobility for Category (IV) tasks. Figure 4:8 %BTs at different numbers of vehicles for Category (III) tasks. Figure 4:9 BTs at different TDs for Category (IV) tasks. Figure 8:0 BTs at different numbers of vehicles for Category (IV) tasks. Figure 8:1 BTs at different TDs for Category (III) tasks.