# JSSTR: A Joint Server Selection and Traffic Routing Algorithm for the Software-Defined Data Center
## 6 Evaluation
### Evaluation Results and Analysis
(2) Network load: The same analysis can be made for the curves given in Figure 6, which shows the network load values when using the JSSTR, WLC-GA and Travs algorithms. As shown in that figure, when the number of arrived users is the same, the network load values of JSSTR are obviously less than those of WLC-GA. For instance, when there are 100 users, the network load of JSSTR is 0.5226, while for WLC-GA, it is 0.6277. In that case, the network load decreases about 20 percent when using JSSTR. Thus, JSSTR can achieve higher efficiency than WLC-GA. Meanwhile, the network load values of JSSTR are almost the same as Travs, which shows that JSSTR can almost obtain the optimal result when calculating the routing path. (3) Network load balancing degree: Figure 7 presents the network load balancing degrees of JSSTR, WLC-GA and Travs. From Figure 7, we can see that JSSTR outperforms WLC-GA and has as good performance as Travs. More precisely, for different numbers of users, the network load balancing degrees of JSSTR are always lower than those of WLC-GA. For instance, when the number of arrived users is 100, the network load balancing degree of JSSTR is 0.1521, while the network load balancing degree of WLC-GA is 0.1757. Therefore, in that case, compared with WLC-GA, JSSTR can decrease the network load balancing degree by about 16 percent. At the same time, the network load balancing degree of Travs is 0.1508, which is very close to the network load balancing degree of JSSTR. It shows that the JSSTR can almost obtain the optimal load balancing degree when calculating the routing path. As previously mentioned, when choosing the destination server, WLC-GA will choose one server from the server cluster without considering the network status. On the contrary, JSSTR will jointly calculate the destination server and routing path. Therefore, JSSTR can improve network efficiency and balance network load. Figure 5: Routing path hop degree comparison for JSSTR, Travs and WLC-GA.  
(4) Server load: From Figure 8, it can be seen that for JSSTR, WLC-GA and Travs, the server loads are nearly same. When the number of users is 100, the server loads of JSSTR, WLC-GA and Travs are 0.5083, 0.5114 and 0.5083, respectively. This indicates that compared with WLC-GA, the impact on server load generated by our JSSTR method is negligible. This is because our JSSTR method calculates the destination server and routing path jointly. Therefore, when choosing the destination server, the server fitness is considered as one of the main factors. If there are servers with a similar load, the server that has more path fitness will be chosen as the destination server, which will not impact the server load. (5) Server load balancing degree: Figure 9 shows the server load balancing degrees of JSSTR, WLC-GA and Travs. The server load balancing degree of JSSTR is very close to that of WLC-GA and Travs. For example, when there are 100 users, the server load balancing degrees of JSSTR, WLC-GA and Travs are 0.0381, 0.0352 and 0.0369, respectively. (6) Calculation time: Figure 10 is the result of the comparison of the computation complexity. In Figure 10, the calculation time is the mean time interval between the controller receiving the user request and successfully handling that user request. In Figure 10, we can see that the proposed JSSTR algorithm has a little increase in calculation time compared with WLC-GA (49.0 ms for JSSTR and  
Figure 6: Network load comparison for JSSTR, Travs and WLC-GA.  
Figure 7: Network load balancing degree comparison for JSSTR, Travs and WLC-GA.  
36.8 ms for WLC-GA). However, the mean calculation times of JSSTR is significantly less than that of the Travs algorithm (412.4 ms). Except these metrics, it should also be noted that in the proposed JSSTR algorithm, the number of memeplexes and number of frogs in each memeplex affect the calculation accuracy and computation complexity of that algorithm.