# Retracted: W-GPCR Routing Method for Vehicular Ad Hoc Networks
## 2 Materials and Methods
### Greedy Forwarding Strategy Based on Weight Selection
#### 2.1.1 Influence of Node Movement Direction on Routing Performance
Each vehicle was equipped with an omnidirectional antenna and accurate positioning service, which can obtain its position coordinates and driving direction. The communication distance of the vehicle was set to 250 m, and the maximum speed of travel was set to 15 m/s. The MAC(Media Access Control) layer protocol model was set to the IEEE802.11p protocol, the channel transmission rate was set to 3 Mbps, and the transport layer protocol model was set to the UDP(User Datagram Protocol) protocol. The sending interval of the hello packet was set to 1 s, the sending interval of the data packet was set to 0.2 s, and the simulation time was set to 200 s. The data traffic of each node pair (source-destination) was regarded as a constant bit rate (CBR), and a fixed 512-byte data packet was generated by setting a constant bit rate [22; 23; 24]. The simulation parameters of the model are shown in Table 2.

Figure 5: Schematic diagram of restricted forwarding strategy. \begin{table}
\begin{tabular}{c c} \hline
**Parameter** & **Value** \\ \hline Packet size & 512 bytes \\ Simulation time & 200 s \\ Simulation area & \(1000\times 1000\) m \\ Bit rate & 5, 10, 15, 20 \\ Maximum rate & 15 mJy s \\ Number of nodes & 20, 40, 60, 80, 100 \\ Hello packet interval & 1 s \\ Transfer Protocol & UDP \\ Packet interval & 0.2 s \\ MAC layer protocol & 802.11p \\ Channel transmission rate & 3 Mbps \\ Communication distance & 250 m \\ \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 6: Schematic diagram of the road traffic model: (**a**) map of Tianyuan District, Zhuzhou City, Hunan Province; (**b**) schematic diagram of road files generated by SUMO. ## 3 Results

In order to evaluate the impact of different amounts of data traffic on the network on routing performance, the number of CBR connections in different node count scenarios was varied between 5, 10, 15, and 20. The weight ratio of the greedy forwarding strategy based on weight selection was set as \(g_{1}=0.7\), \(g_{2}=0.2\), and \(g_{3}=0.1\). The weight ratio of the repair strategy based on weight selection was set as \(r_{1}=0.2\), \(r_{2}=0.7\), and \(r_{3}=0.1\). Through 30 simulation runs, the average values of all simulation data were taken, and a 95% confidence interval was set. Data are finally presented in the form of an error bar graph. The performance indicators used in the simulation are defined as follows:

* Packet delivery rate: the ratio of the total number of packets received by the target node to the total number of packets sent by the source node. \[\text{Packet deliver rate}=\frac{N_{\text{receive}}}{N_{\text{send}}}\]
* Average end-to-end delay: The average delay of all successfully received packets. \[\text{Average end-to-end delay}=\frac{\sum_{1}^{n}D_{n}}{n}\]
* Average hop: the average number of hops of all nodes in the network. ### Packet Delivery Rate

Figure 7 shows the packet delivery rate of different numbers of nodes and CBR connections. As the number of nodes in the network increases, the connectivity of the network is improved, and the probability of encountering routing holes is reduced. Therefore, with the increase of the number of nodes in the network, the packet delivery rate of these three routing protocols increases. In networks with different numbers of nodes and different CBRs, the packet delivery rate of W-GPCR is higher than that of GPCR and GPSR. In sparse networks with CBR of 10 and 20, and nodes numbering 20, 40, and 60, the packet delivery rate of W-GPCR is much higher than that of GPCR and GPSR. Because the repair strategy of W-GPCR weight selection selects the next-hop node by weight, rather than simply relying on the right-hand rule to traverse the node, routing redundancy is reduced, data packets are prevented from being delivered away from the target node, and the stability of the system is improved. Figure 7: _Cont._

### Average End-To-End Delay

Figure 8 shows the average end-to-end delay for different numbers of nodes and CBR connections.