# Research on Routing Algorithm of Construction Robot Cluster Enhanced Ad Hoc Network
## 4 Simulation Experiments
From Figure 11, it can be seen that the robot nodes survived more nodes per round at 0.5 m/s moving speed, and there were still 38 nodes surviving at 1000 rounds, two nodes surviving at 1000 rounds at 1.0 m/s moving speed, and all nodes died in the 631 st and 873 rd rounds at 1.5 m/s and 2.0 m/s moving speed, respectively. A comparison experiment was conducted with the other two algorithms at a node movement speed of 0.5 m/s, as shown in Figure 12. The curve can be described as the gradual failure of nodes due to energy depletion as the number of iterations increases. The first node death rounds of this paper algorithm, FFACM algorithm, and reference [36] algorithm were 906, 305, and 458, respectively, while the last node death rounds were 1830, 1490, and 1620, respectively, and the ACER algorithm improves 22.8% and 13% in algorithm performance compared to the FFACM algorithm and literature [36] algorithm, respectively, effectively extending the network life cycle. Figure 8: Network topology diagram. (a) Original topology of network nodes; (b) Optimized topology diagram. Figure 9: Relationship between the network connectivity and number of nodes [36]. Figure 11: Number of surviving nodes per round at different moving speeds. Figure 12: Network lifetime [36]. Figure 10: Average link quality [36]. To verify the performance of the algorithm in this paper in a highly dynamic environment, the end-to-end delay at different packet rates was designed, as shown in Figure 13. End-to-end delay determines the adaptability of communication networks to topology changes. Although there is no clear end-to-end delay standard for self-assembled networks in industrial construction scenarios, the lower the latency, the more efficient and secure the communication network can be. The nodes move at the speed mentioned above of 0.5 m/s, and 4000 bit fixed-length packets were used for simulated communication, with each CBR (Constant Bit-Rate) source sending packets at rates ranging from 1 packet/s to 5 packet/s. As the CBR source sending packet rate increases, the end-to-end delay of the FFAMCM algorithm and reference [36] algorithm's end-to-end delay in this paper also increases, which is due to the increase in packet rate that increases the network load. However, compared to the other two algorithms, this algorithm has a better performance. The algorithm in this paper has a stable performance because it combines the dynamic characteristics of nodes in the routing phase and considers the effects of load, residual energy, and hop count on routing, i.e., the subsequent hop nodes were selected with slower movement, lower congestion, higher energy, and fewer hops. Based on the previous experiments, the end-to-end time delay comparison experiments were set up to verify the algorithm's performance under different periods based on the characteristics of construction robots, which need to stay in different locations to complete related tasks such as construction, as shown in Figure 14. The nodes move at 0.5 m/s with 4000 bit fixed-length packets, the CBR source sends packets at 1 packet/s, and the simulation time is 400 s. As the pause time increases, the end-to-end delay of the algorithm in this paper, the FFACM algorithm, and the algorithm in reference [36] decrease continuously. However, the algorithm in this paper is significantly better than the other two algorithms, the increase in pause time causes node mobility to decrease, and the previous content has shown that the routing algorithm in this paper integrates several factors in routing node selection, so it is more adaptable to the dynamic changes of self-organized networks. Figure 10.0 End-to-end delay at different packet send rates [36].