# Beacon-Based Hybrid Routing Protocol for Large-Scale Unmanned Vehicle Ad Hoc Network
## 2 Beacon-Based Multi-Agent Network Hybrid Routing Algorithm
### Path Discovery and Maintenance
#### 2.2.1 Path Discovery
The RL of the beacon-based routing protocol was only related to the time allocated to the first three phases of the pulse unit and unrelated to the number of nodes and communication link data. Therefore, using the beacon-based routing protocol for network unmanned equipment was more stable and suitable for the LUVN scenario. (3) Effect of Pulse Cycle on the Network

In the beacon-based routing protocol, periodic flooding was used to create and maintain the OPT for nodes in the network to reach the beacon node. At the same time, nodes in the network completed path establishment and data transmission according to the guidance of the path tree. The sending period of the pulse message of the beacon node determined the network entry time and path update maintenance time of nodes in the network. The sending period of the pulse message should be selected according to the number of nodes in the network, the network access time, communication bandwidth, and other parameters required by the network. Figures 9 and 10 were the simulation comparison of PDR and RL when the pulse cycle was 1.5 s, 2 s, 2.5 s, and 3 s, respectively, under the configuration parameters in Table 1.

Figure 8: Routing load of beacon-based routing and the AODV and DSDV protocols. As shown in Figure 9, the four curves represented the PDR of beacon-based routing protocols with pulse cycle of 1.5 s, 2 s, 2.5 s, and 3 s. The result showed that the PDR of the beacon-based routing protocol was the most stable when the pulse cycle was 1.5 s, and the performance would gradually decrease with increasing time. The simulation result showed that the active link continuously sent data in the active time; due to constant motion of the node in the path, path failure would occur. Therefore, the shorter the time interval of the pulse cycle, the better the perception of the change of link path failure can be. Therefore, the delivery rate is the best when the pulse cycle is 1.5 s, and the delivery rate decreases gradually with the increase in time. The beacon-based routing protocol made full use of the periodic pulse message, completing the path reconstruction and path addressing operation within a pulse cycle, which effectively avoided the problems of path failure and repeated path finding. As shown in Figure 10, the four curves represented the RL of beacon-based routing protocols with pulse periods of 1.5 s, 2 S, 2.5 s, and 3 s. The simulation result showed that with the increase in pulse cycle, the RL decreased gradually, which was also consistent with the design idea of this paper. Theoretically, the RL of the beacon-based routing protocol is only related to the time allocated to the first three phases of the pulse unit and unrelated to the number of nodes and communication link data. The simulation verified this: the larger the pulse cycle, the smaller the proportion of time occupied by the route load; the smaller the route load, the larger the effective data bandwidth. Figure 10: Comparison of pulse cycle routing load of beacon routing protocol. Figure 9: Comparison of pulse cycle delivery rate of beacon routing protocol. ## 4 Conclusions

Aiming at the problems of path failure, repeated routing path finding, and excessive cost of route maintenance in the networking of large-scale unmanned equipment using traditional routing protocol, combining the characteristics of active and on-demand routing protocols, we proposed a beacon-based hybrid routing protocol for LUVAN. In this beacon-based routing protocol, the path tree of each node pointing to the beacon node was used as guidance. Nodes were periodically maintained for OPT. Source nodes used unicast mode to create paths as required. Active nodes actively maintained routing paths in the network, maximized routing control commands, and limited the route load to a fixed time. Therefore, the cost of route maintenance in unmanned equipment network is reduced and the problems of path failure and repeated path finding are solved.