# An Energy-Balanced Geographic Routing Algorithm for Mobile Ad Hoc Networks
## 4 Simulation  
In this section, we compared the performance of the proposed strategy with several geographic routing algorithms. Among them, GPSR is a classic ad-hoc routing algorithm based on the geographic  
Figure 6: Format of the improved HELLO packet. Figure 7: Flowchart of the EM-GPSR routing protocol. location. SU-GPSR is a routing protocol that considers energy consumption balance and the mobility of nodes. Firstly, on the basis of the mobility of nodes and the remaining lifetime of the link, the candidate nodes are divided by the threshold, and then the node above the threshold is selected according to the weight of the measurement. GPSR, SU-GPSR, Improved Energy and Mobility ACO (IEMACO) and the proposed EM-GPSR routing strategy are simulated and analyzed with the OPNET network simulation tool, and the simulation parameters are set up as shown in Table 1.  
Figure 8 shows how the average end-to-end delay of different routing algorithms varies with the speed at which the node moves. It can be seen from Figure 8 that as the node moves faster, the average end-to-end delay increases. Moreover, the end-to-end delay of the topology-based routing protocol is obviously higher than that of the protocol based on geographic location. This is because topology-based routing protocols are passive, where routing discovery is only carried out when data transmission is needed. Moreover, when the node has mobility, the routing information obtained by the neighboring node may be outdated, and the node has to rediscover the route before the data transmission. In the three geographic routing protocols, GPSR has the best latency performance when the node moves at a low speed. This is because GPSR uses greedy forwarding, and the criterion for each selection is to pick the node closest to the destination node, while for SU-GPSR and EM-GPSR, in addition, the mobility and energy of the node are also considered. Therefore, the next hop is not necessarily the closest to the destination node, and so the delay is increased. However, with the increase of node movement speed, the delay performance of the EM-GPSR algorithm proposed in this paper is obviously better than SU-GPSR and IEMACO. This is because EM-GPSR fully considers the mobility and energy consumption rate of nodes. The \"area\" is divided according to the remaining lifetime of the link, and a link with a longer lifetime is selected to ensure the stability and continuity of data transmission and to reduce the end-to-end delay. Figure 9 shows the curve of the packet delivery rate for different routing protocols with varying node movement velocity. It can be seen from the figure that the packet delivery rate in the network decreases with the increase of the node movement speed. The GPSR packet delivery rate is the lowest since GPSR only uses greedy forwarding, and the stability of the selected link may not be as good as other algorithms. When the node movement speed is less than 20 m/s, the packet delivery rate of IEMACO is slightly higher than that of EM-GPSR. When the node movement speed is greater than 20 m/s, the IEMACO packet delivery rate drops significantly and is smaller than EM-GPSR. As in the topological routing protocol IEMACO, when a node finds that the next hop does not exist, the process of routing rediscovery is longer. Moreover, the faster the topology changes, the more frequently the routing is discovered, which can cause packets to be discarded. However, with the increase of node movement speed, the packet delivery rate of the EM-GPSR algorithm can be significantly higher than SU-GPSR and IEMACO. This is because EM-GPSR takes the mobility of the node as the primary consideration, and chooses the link with a long remaining lifetime to transmit the data, which improves