## 4 Evaluation
IPERF was used to generate TCP and UDP traffic between hosts H1 and H14 to simulate a scenario where an application transfers data among hosts. The test used several optimization criteria to select the path (these are described in Table 4). Paths shared by host-to-host routing methods have different network metrics. Our proposal computes and configures the path considering all available QoS parameters in the network. The algorithm can be configured depending on the requirements of a particular application, but in this case, the path minimizes the parameters considered. This evaluated comparison between algorithms shows the capacity of the selected path for each. Next, we discuss each algorithm regarding the chosen path and how it affects the network performance results. As seen in Table 4, the average data transfer speeds of the traditional methods are slower (minimum hops 23.8 Mbps and maximum available bandwidth 38 Mbps) than the path selected by our method (66.9 Mbps), as were the paths with the lowest delay (53.4 Mbps) and packet loss (63.1 Mbps). For the test, we used the exact Dijkstra search algorithm to show the efficiency of different paths with optimization criteria according to the parameters usually implemented in traditional routing: fewer hops and higher bandwidth. We also added the path with the minimum delay and data loss. The path with the \(H\) (fewest hops, most frequent routing) had the lowest average data transfer rate because it had little effective traffic. A significant portion of its traffic had to be retransmitted because its path went through several nodes where there would have been significant losses, making it the worst path in this test. The path with \(B\) (the highest available bandwidth) had the highest number of hops and a high probability of packet loss and delay because it had to go through many nodes to reach its destination. The path with \(PL\) (the least packet loss) had a higher traffic transfer rate than the previous paths. However, it was the path with the most packet retransmissions due to packet delays, significantly affecting performance. The path with \(w_{B,D,PL}\) (weighted sum), considered the weight by the available metrics, achieved better performance than the traditional methods. From the obtained results, we can see that an evolutionary algorithm (MOCell and MOEA/D) can improve the routing-related aspects by evaluating multiple available paths for establishing routing flows and evaluating their QoS parameters. The path performance is determined by the amount of data successfully transmitted during the cycle period (Equation (5)). We can evaluate the throughput in terms of the maximum data transmission capacity in the network to normalize the throughput size of each path and calculate the area enclosed by the throughput function (Figure 10) using the Riemann sum [46]. We find that the path proposed by \(Min_{f_{1},f_{2},f_{3}}\) (MOCell) can exploit 71.08% of the network throughput on average, and MOEA/D can exploit 69.23%, while the paths selected by the other techniques had values below 55.99% (see Figure 10). The MOCell-based routing path improves by more than 54% on average compared with the traditional routing method with fewer hops (\(H\)) and by 35.44% for the path with the highest available bandwidth (\(B\)), in the case of the network topology presented in this paper. Finally, in the case of the evolutive algorithms, MOCell had a 1.85% higher throughput than the MOEA/D method when using the same parameters and metrics for mutations, generations, and the method of selecting individuals by tournament; in this way, a fair evaluation was obtained. The path chosen by the MOCell method shows slightly better performance than the MOEA/D method, especially in the first 30 s of transmission, since it converges earlier. After this period, both methods show similar performance. Figure 11 and Table 5 show the values of the throughput area (normalized by the maximum capacity) of 30 independent runs of the Mininet experiment for each path selected by the algorithms.