# A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks
## 3 The Improved Multipath Routing Algorithm
### RLLMR Algorithm

Table 3: Simulation parameters. with the traditional route discovery algorithm is affected by the arrival rate to a greater extent than with the route discovery algorithm under static configuration; that is because the traditional route discovery algorithm needs to multiple-forward RREQ messages, resulting in spending a long time finding the destination node routing information, while the route discovery algorithm based on the static configuration scheme can obtain the routing information of the destination node through intermediate nodes to effectively reduce the number of RREQ forwarding. Consequently, this method can greatly reduce route discovery latency. As shown in Figure 7, the AODV route discovery latency and the AOMDV route discovery latency fluctuate as the mobile node approaches the station, which is due to the change in the number of RREQ message forwarding, that is, the hop count to reach the destination node during the movement of the node. It shows that the hop count is the main influencing factor for the route discovery latency. Therefore, configuring static route information can effectively reduce route discovery latency by reducing the number of route discovery request forwarding. In this simulation, packet No. 1 represents the high-latency requirement service, such as train operation control (OCS), packet No. 2 represents the medium-latency requirement

Figure 6: The relationship of discovery latency with arrival rate. Figure 7: The relationship of discovery latency with mobile node location. service, such as train operation status monitoring (TOSM), and packet No. 3 represents the low-latency requirement service, such as passenger multimedia service (PMS). The simulations are compared using the traditional AOMDV algorithm and AMS algorithm to transmit these three types of services separately, and the simulation results of the end-to-end latency are shown in Figure 8.

From Figure 8, it can be seen that the multipath selection algorithm with adaptive adjustment of the number of paths based on the service latency requirements can reduce the impact of the arrival rate on the end-to-end latency within a certain extent, and the average end-to-end latency of transmitting the same service data with the AMS algorithm is lower. Based on the data statistics, the average end-to-end latency of the proposed AMS routing algorithm is 28.48% lower than that of the traditional AOMDV routing algorithm. However, when the arrival rate keeps increasing, the average end-to-end latency also increases exponentially. With the AMS algorithm, this paper also employs the local route maintenance scheme and compares the average end-to-end latency using the LRM scheme and the traditional AOMDV, which uses the alternate path repair scheme under different network quality environments. The simulation results are shown in Figures 9 and 10. Figures 9 and 10, respectively, describe the variation in the average end-to-end latency of the mobile nodes during their movement toward the station sink node in good and bad network environments. From the figures, it can be seen that the average end-to-end latency of the AODV routing algorithm is the highest in the case of the same number of packets transmitted. It is because the AODV routing algorithm does not engage in routine maintenance but rather restarts the route discovery to find a new path for retransmission when a link failure is discovered, which consumes a lot of route discovery time. In the case of a poor network environment, the AODV routing algorithm also has a high average end-to-end latency, which is because the link failures happen frequently in bad network environments such that alternate paths need to be enabled frequently for retransmission, which consumes a lot of repair time. On the contrary, in the LRM scheme, it is not necessary to go back to the source node to use alternate paths, but to perform local repair with the help of maintenance nodes, the repair latency of this scheme decreases compared to the AODV routing repair latency by about 23.81%.