## 6 Simulations and Result Analysis
### Simulation Results and Analysis
#### 6.2.3 Effect of Traffic Loads  
To investigate the influence of traffic loads on algorithm performance, we present the PFs obtained by two algorithms with different traffic loads and the same core numbers, as shown in Figures 17-19.  
First, we can see the whole variant trend of PFs obtained by the two algorithms. As the number of connection requests increases, the PFs obtained by the two algorithms become worse (away from the origin of coordinates), i.e., the blocking ratio and crosstalk ratio are getting higher. This is because network resources are limited. When the number of requests increases, the average resource that the network can provide for each latter request decreases, causing some requests to be blocked, and the allocation of unblocked requests leads to an increase in the crosstalk ratio.  
Second, we compare the dominant performance of the solutions obtained by the two algorithms under different traffic loads. For the same number of cores, the proposed algorithm can obtain a certain number of dominant solutions under both light and heavy traffic loads. This is due to the influence of core switching and the multiple adaptive strategies proposed, which enable the algorithm to conduct a comprehensive and efficient search in the overall resource space of the network. In addition, it can be seen from the first two figures that as the number of requests increases, the number of dominant solutions obtained by the proposed algorithm decreases, i.e., the efficiency of core switching gradually weakens. This results from core switching under light traffic loads which can consider the available spectrum resources of each core from the perspective of the entire network, so that more requests can be served under the spectrum constraints, thus reducing the network RBR. However, under heavy traffic loads, the efficiency of core switching becomes weak, since the negative impact of network spectrum fragments is the main factor in the algorithm's performance, i.e., many spectrum fragments will appear on all cores. Even if the core can be switched on different links, the spectrum constraints of continuity and consistency cannot be satisfied, resulting in an increase in both the network RBR and crosstalk ratio.  
Finally, the performances of the two algorithms in terms of solution diversity are compared. It can be seen from the figures that the diversity of the solutions obtained by the proposed algorithm is better, and it can find solutions that cannot be obtained by the baseline algorithm in the objective space with a smaller blocking ratio (left half of figures), which shows the same rule as that in Figures 14-16.  
With the increase in both the number of connection requests in Figures 14-16 and the number of cores in the last two figures, we can see that, except for the scenarios with 7-core, most of the solutions of MOEA/D-AMSF dominate those from the baseline algorithm. Each lower right part of the three pair-curve shows that the baseline algorithm obtains more solutions, particularly in the case of three cores. However, such solutions have a blocking ratio of 0.4 or even higher, and thus are infeasible in real systems.