## 5 Performance Evaluation
### Experimental Results  
As illustrated in Figure 5, the average completion time of the DRPS approach is the lowest because the DRPS approach performs task migration on multiple paths simultaneously. When the task migration on one of the paths is successful, the tasks on the other paths will be discarded to reduce the cost. The migration time of the DRPS/F approach is the lowest after the DRPS approach because DRPS/F does not take into account the performance fluctuations of ES, resulting in a higher failure rate of task migration than the DRPS approach takes more time. The migration times of Greedy-SP, Greedy-CP, and PLP approach are similar and significantly higher than DRPS and DRPS/F approach. Because the three do not consider the performance fluctuations of ES in the process of task migration, the PLP algorithm is jointly optimized with Pareto, so the migration time is slightly lower than the other two algorithms. Task completion rate is an important criterion to measure the migration algorithm. A too long task migration time will affect QoS, but task migration failure will have serious consequences. As illustrated in Figure 6, the TCR of the DRPS approach and the DRPS/F approach is significantly higher than that of the other three algorithms. The reason is similar to that of the ACT. The DRPS approach dynamically updates the failure rate of ES in real-time, and the failure rate of each migration path is always the lowest. This ensures that the TCR of the DRPS approach is always better than the comparison algorithm. The AFC can reflect the overhead of the algorithm. The higher the AFC, the more tasks that need to be retransmitted during the migration process, and the greater the natural  
Figure 5: Results of the ACT. Figure 6: Results of the TCR. overhead. In order to measure the performance of the algorithm more accurately, we further divide the DRPS approach and the DRPS/F approach into DRPS/OP, DRPS/AP, DRPS/F/OP, and DRPS/F/AP. As illustrated in Figure 7, DRPS/OP and DRPS/F/OP represent the AFC in the successful migration path. It can be observed that the performance of DRPS/OP is better than other algorithms in five rounds of testing. DRPS/AP and DRPS/F/AP represent the AFCs in all migration paths (including unfinished migration paths), and it can be observed that their performance has decreased. Still, this performance loss is accepted to ensure service migration's reliability. As can be observed from Figures 5 and 6, with the increase in task volume, the performance of DRPS approach remains stable without obvious fluctuation, indicating that the DRPS approach has good robustness in ACT and TCR. Although the performance of DRPS approach on AFC fluctuates with the increase in data volume, it is also within the acceptable range. Overall, as illustrated in Table 2, compared with the DRPS/F approach, the performance of ACT and TCR of the DRPS approach is improved by 2.03% and 2.13%, respectively; compared with Greedy-SP, the performance of ACT, TCR, and AFC is improved by 19.17%, 14.02%, and 4.18%, respectively; compared with Greedy-CP, the performance of ACT, TCR, and AFC is improved by 22.41%, 15.61%, and 6.01%, respectively; compared with the PLP algorithm, the performance of ACT, TCR, and AFC was enhanced by 17.45%, 13.17%, and 7.22%, respectively; compared with the DRPS/F/OP and DRPS/F/OP approach, the performance AFC was enhanced by 2.97% and 11.6%, respectively (compared with the DRPS/OP). This is because the DRPS approach selects a set of paths for service migration according to the real-time error rate of ES, and combines replication and resubmission strategies during the migration process to ensure that the service always has the least migration time, compared with traditional PLP and Greedy, etc. The ACT, TCR, and AFC performance of the DRPS approach has been significantly improved.