## 3 Preliminaries and Definitions
### Agdoa Algorithm
#### 4.2.2 DOA Considering Greedy Strategies
### Performance of BSSA

#### 6.1.1 Impact of the Number of Mobile Users

In this section, we set the base station with the same computational power, i.e., Rn = 70 GHz, and all mobile user offloading tasks were configured with the same request conditions, wq = 1500 (Megacycles), lg = 700 KB, Tgq = 0.5 (s), Tbg = 0.65 (s). We output the welfare of the system after it had run, in order to assess the effectiveness of the solution to the resource offloading and computational resource scheduling problem; that is, the performance of the fitness function JRORS, under the influence of various numbers of mobile users. To assess the efficiency and performance of the system, we took into account the system response rate, and to assess the fairness of the system, we took into account the SSD. NGO, BPSO, GA, and BSSA are all suitable algorithms for solving discrete optimization problems. From Figure 2(a), we can observe that NGO and GA showed an overall increasing trend in welfare with the increase in the number of mobile users, but there was oscillating instability. BPSO and BSSA showed a flat increase in welfare with the increase in the number of mobile users. This was because, as the number of users increased, more requests may be generated in the system, and when these requests are reasonably handled and satisfied, the total utility of the system may increase. In terms of welfare performance, NGO performed poorly, which means that NGO cannot achieve good results for the JRORS problem. BSSA had a larger welfare with a different number of mobile users, which means that BSSA can obtain a better solution when multiple factors are considered for scheduling computational resources. Compared to GA, the proposed BSSA improved by about 100% for welfare when the number of mobile users was 12 and by about 20% when the number of mobile users was 100. The complexity of the problem grows exponentially as the number of users increases. Both BSSA and GA needed to search the large-scale solution space, and hence the size of the BSSA boost became smaller. However, due to the addition of binary, the complexity of BSSA decreased on the discrete problem JRORS, so it was easier to search for a better resource allocation scheme for welfare. Figure 2(b) illustrates that BPSO and BSSAhad a larger system responsiveness, and BPSO's system responsiveness did not change much for different numbers of mobile users. Compared with BPSO, BSSA had almost a 1x improvement in the corresponding rate when the number of mobile users was 12. BSSA's response rate naturally decreased slightly with the increase in the number of mobile users, due to the consequent increase in the search space and the complexity of the problem, but it still managed to maintain a higher response rate, which also reflects the scalability of BSSA. Compared with BPSO, at a mobile user number of 100, BSSA improved in its response rate by about 40%, which was due to the fact that the search strategy of BSSA is more suitable for the JRORS problem. From Figure 3c, it can be seen that the SSD of BSSA and GA was larger in most of the cases in the comparison experiments, which proved that the fairness of BSSA was better. Moreover, the SSD of BSSA decreased smoothly with the increase in the number of mobile users, which proved that BSSA had the best fairness when the number of mobile users was small. This is due to the fact that competition among a large number of users may lead to more competitive resource allocation. This may result in certain users always having a dominant position, while other users are unable to obtain a fair share, thus reducing the fairness. At the same time, since the SSA algorithm has the unique advantage that the group tends to move in the direction of greater comfort, this leads to a smooth, progressive search process that avoids drastic fluctuations, and the experiments yielded smooth changes for each of the performance metrics as the number of mobile users was varied.