## 5 Simulation and Evaluation
### Impact of Network Size  
The network throughput is the critical metric that illustrates the network scalability. For the scalability of a network, its capacity should grow linearly with the number of nodes. Furthermore, increasing the network size should not lead to performance degradation [3; 4]. The main reason for the lack of scalability in routing protocols that run on multi-hop wireless networks is that the packet has to travel long distances,  
Figure 8: Throughput vs. nodes speed.  
Figure 9: End-to-end delay (seconds) vs. nodes speed.  
roughly \(n^{1/2}\) hops, causing the bandwidth consumption per packet to rise rather quickly as the number of nodes increases [32].  
Figure 11 shows the throughput performance evaluation as a function of the number of nodes. The FQ-AGO shows a considerable advantage over other routing protocols. FQ-AGO considers the distance progress, available throughput, transmission power, and node-link quality in the candidate selection process. Accordingly, it enhances the network performance by maximizing the one-hop node performance along the path, as one hop performance improvement contributes to the end-to-end performance. On the other hand, the throughput on AODV is low due to the rapid loss of wireless connections with neighbors as the network topology changed and network size grows, the routing control messages drastically increase, which generates considerable overhead in DSDV and AODV. The requirement of pre-computed routes in DSDV and AODV improves network connectivity at the expense of routing performance. Therefore, the throughput decreases linearly as the number of nodes increases. Regarding the packet delivery ratio, as shown in Figure 12, FQ-AGO demonstrates consistent performance in all network environment configurations due to selecting the most stable and effective candidate along the path to the destination, which leads to high packet delivery ratio. By contrast, for DSDV and AODV, the packet delivery ratio decreases drastically, because of the frequent link breakage, which requires initiating a route search to update the routing table. That increases the control messages' overhead and congests the network; the time-out it takes to update the routing table increases the end-to-end packet delay and remarkably decreases the packet delivery ratio.  
Figure 13 shows the average hop-count as a function of increasing the network size. Intuitively, the hop-count relies on the number of intermediate nodes participating in the packet relaying process. The results offer higher resolution and a clear relation between the number of nodes and the average hop-count. FQ-AGO takes advantage and makes full use of candidates that can transmit the packet for long distances. In other words, nodes with broad transmission range can reach the destination in fewer hops. On the other hand, DSDV and AODV both show an increase in the number of hop-counts to relay the transmitted packet. For example, DSDV calculates the shortest path to the destination; however, DSDV overlooks the presence of asymmetric links and relies on homogeneous candidates with the same transmission capability. In AODV, there is a noticeable routing performance degradation due to the rapid  
Figure 10: Packet delivery ratio (%) vs. nodes speed.  
change in the network topology, a massive overhead initiated by intermediate nodes along the path to find a new path to the destination. The recovery process from losing end-to-end path comes with an extra cost of increasing delays and launching high overhead, which decays the overall network performance and, in the worst-case scenario, the percentage of dropped packets increases consequently.  
Figure 11: Total throughput vs. number of nodes.  
Figure 12: Packet delivery ratio (%) vs. number of nodes.