# Adaptive Virtual RSU Scheduling for Scalable Coverage under Bidirectional Vehicle Traffic Flow
## 6 Performance Evaluation
### Vehicle-Level Online Implementation  
In this section, we will present the vehicle-level simulation to evaluate our proposed adaptive bidirectional scheduling strategy (ABS for short). Given a specific road segment, we assume that the number of vehicles entering the road segment follows a Poisson distribution with parameter \(\lambda\). When the vehicles are driving along the road, they can have V2I communications with RSUs or V2V communications with other vehicles in 6 Mbps bandwidth and 400 m communication range. We also assume that the total number of replicas is 10,000, and the file size of each replica is 200 m on average. The storage capacity of each RSU is 10T, which means that a single RSU can replicate 500 different replicas approximately. In addition, the storage capacity of each vehicle is 1T, which means a single vehicle can replicate five different replicas in a carry-and-forward manner. The experiment configuration is listed in Table 2. To evaluate the performance, we use a cellular based strategy as the benchmark, in which the vehicles will resort to the long-range communications through a cellular network. In addition, we have some other strategies for comparison. PROPHET is a prediction based  
Figure 12: Cumulative distribution functions with different RSUs.  
solution for intermittently connected networks [28]. The V2X based approach is a comprehensive solution with V2V and V2I communications to reduce the time delay [29]. DBC is a density-based multilevel clustering algorithm to formulate stable and long living clusters for VANETs [30]. CMCS is a connectivity-oriented maximum coverage RSU deployment scheme, which aims to maximize V2I communication performance in urban areas [14]. HE is a heuristic solution with greedy algorithm for the highway scenario [15].  
In the vehicle-level simulation environment, we compare the cost saving and time delay in Table 3. Specifically, the cost savings refer to the content delivery through V2I or V2V rather than cellular communications. These strategies are implemented in a two-hour simulation for the performance on average and worst case. PROPHET and DBC are implemented with multi-hop data dissemination in VANETs environment. Without the support of RSUs, we can see that PROPHET and DBC have a lower performance on cost savings and time delay than RSU-based solutions. Specifically, our proposed strategy has higher cost savings than V2X, while V2X can reduce time delay more efficiently. We can conjecture the reason that our proposed ABS is designed to improve the global RSU resources utilization efficiency, and V2X is designed to reduce time delay with the combination of V2I and V2V communications. In addition, CMCS and HE can have 60.3% and 55.2% with RSU deployment. Both of them assume the highway scenario in which all the vehicle traffic follows in the same direction, without considering the V2V communications in bidirectional traffic flows. Obviously, our proposed solution with highest cost savings is more V2V friendly, in spite of a long time delay to balance the content allocation priority.