## 6 Performance Evaluation  
The single-tier scheme, LTE4V2X [26], and the proposed framework were implemented in the Qualnet 5.0 [36] simulator to compare their performance in terms of the sensing data transmitted via 3G/LTE and the number of 3G/LTE connections. For fairness, we only cumulated the amount of cyclist sensing data uploaded and global fleet information downloaded by the group headers in LTE4V2X. The total number of cyclists in the fleet network varied from 30 to 150. We randomly placed all cyclists on a common cycling path and randomly set their moving speeds from 20 to 40 km/h every 100 m. The network interface of IEEE 802.11b with two-ray ground radio model was adopted and its maximum transmission range was 283 m in Qualnet (for open spaces with line of sight). The ratio of aggregated and raw data sizes for a cyclist's sensing information was 0.25. Each cyclist updated her/his sensing data every 5 s and each gateway broadcasted an IAB every 5 s. \(\theta\) was set to 5 and the simulation time was 900 s. Each simulation was repeated 100 times and the average value was taken. Simulation parameters are summarized in Table 2.  
Figure 4a illustrates the sensing data transmitted via 3G/LTE under different numbers of cyclists. The total numbers of cyclists were set to 30, 60, 90, 120, and 150. In Figure 4a, it can be observed that our scheme transmitted many fewer sensing data via 3G/LTE; only one-fourth and one-third of the sensing data transmitted of the single-tier scheme and LTE4V2X with 150 cyclists, respectively. This is because our scheme can locally collect member sensing data and only the gateway has to transmit the aggregated sensing data to the server via 3G/LTE. In addition, global fleet information is only downloaded by the gateway via 3G/LTE and then broadcast to group members via multi-hop forwarding in the low-tier network. In contrast, the single-tier scheme requires all cyclists to \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline Simulation time & 900 s \\ Number of cyclists & 30\(\sim\)150 \\ Cycling speed & 20\(\sim\)40 km/h \\ Network interface & IEEE 802.11b \\ Path loss model & Two Ray (n = 2) \\ Frequency band & 2.4 GHz \\ Channel bandwidth & 20 MHz \\ Carrier sensing threshold & \(-\)88 dBm \\ Transmission range & 283 m \\ Rate adaptation mechanism & Auto Rate Fallback (ARF) \\ Data aggregation ratio & 0.25 \\ Data update interval & 5\(\sim\)25 s \\ Number of simulation runs & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 3: Comparisons of simulation and analytical results. transmit their sensing data to the server and receive fleet information from the server via 3G/LTE, and LTE4V2X has more gateways to transmit sensing data without data aggregation and to download fleet information than our approach. Therefore, both schemes have to transmit many sensing data via 3G/LTE with numbers of cyclists. Figure 4b shows the number of 3G/LTE connections made for different numbers of cyclists in the fleet network, where many TCP connections result in a long round-trip time of packets [37]. As the number of cyclists increases, the numbers of 3G/LTE connections for the single-tier scheme and LTE4V2X increase exponentially, but the number of 3G/LTE connections for our scheme only increases linearly. The single-tier scheme and LTE4V2X require establishing larger numbers of 3G/LTE connections than our scheme because all cyclists and numbers of gateways have to create connections to the server, respectively. In our scheme, few gateways have to make connections to the server, thus the number of 3G/LTE connections is minimized. Note that the impact of road topology is small on the proposed framework because the fleet cyclists ride along the same cycling path and have the same turning direction at intersections or T-way roads. In addition, the signal fading and multi-path effects of cycling routes in rural and suburban areas are less than those of driving routes in urban areas with high buildings [38; 39].