## 4 Discussion
### Results and Analysysys  
Figures 7 and 8 show the variations of the Average Delay and the Request Success Ratio in the case of different content sizes. As illustrated in the graphs, the request delay of vehicles increased and the probability of content success transmission decreased as the content size increased. This is because larger content requires more time to be transferred by V2V or I2V, and the transmission process fails more easily. Compared with the strategy described by the authors of [19], our strategy has a lower request delay and higher probability of content success transmission, and the gap between the two strategies increases as content size increases. Because our strategy caches content chunks at multiple vehicles in a cluster, request vehicles can obtain content chunks from vehicles in the cluster one by one, which increases the transmission duration between vehicles. Our strategy also adopts the multiuser multichannel transmission mode in the communication process between clusters to solve the problem of the communication duration being too short to complete the content transmission. Figure 8 also demonstrates that the theory value and the simulation value of the Request Success Ratio were similar to each other. The former was slightly higher than the latter, and the gap increased as content size increased. This is because we assumed that the process of the request vehicle obtaining content chunks from different relay vehicles in the cluster was independent in case 3 of our theory analysis. However, as the content size increases, the process between the request vehicle and relay vehicle may wait to begin until the last process is over, which make the theory value higher than the simulation value. Figures 9 and 10 show the variations of the Average Delay and the Request Success Ratio in the case of different vehicle caching sizes. Vehicle caching size is used to describe the maximum capability of the vehicle's caching space. As depicted in the figures, the request delay of vehicles decreased and the probability of content success transmission increased as the caching size increased. This is because increasing the caching size enlarges the probability that a vehicle can find desired content in neighboring vehicles. Compared with the strategy described by the authors of [19], our strategy has a lower request delay and higher probability of content success transmission. Because our strategy caches content chunks at multiple vehicles in a cluster, request vehicles can obtain content chunks from vehicles in the cluster one by one, which increases the transmission duration between vehicles. Our strategy also adopts the multiuser multichannel transmission mode in the communication process between clusters to solve the problem of the communication \begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline The number of content & 200 \\ The size of content (Mbit) & 600 \\ The parameter of Zipf Distribution & 1 \\ The transmission power of vehicle (mW) & 200 \\ The transmission power of RSU (mW) & 2000 \\ The coverage range of vehicle (m) & 50 \\ The coverage range of RSU (m) & 100 \\ The length of lane (m) & 2000 \\ The width of lane (m) & 7 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. duration being too short to complete the content transmission. The probability that a vehicle can obtain content with participation of RSU decreases as vehicle caching size increases, which weakens the advantages of our strategy, so the gap in performance between those two strategies decreases as caching size increases. Figure 10 also indicates that the theory value and the simulation value of the Request Success Ratio were similar to each other. The former was slightly higher than the latter, and the gap increased as the vehicle caching size increased. This is because the probability that a vehicle will obtain content from neighboring vehicles increases as vehicle caching size increases.