# Caching Placement Optimization Strategy Based on Comprehensive Utility in Edge Computing
## 5 Experiment and Analysis
### Experimental Results and Analysis  
1. Impact of different cache sizes on the algorithmic performance To evaluate the impact of different cache capacities on the algorithm's performance, the cache capacity of each server was set to vary between 30 and 60 data blocks. A total of 200 tasks were simulated to be executed by users. The impact of different cache capacities on the cache service rate generated by the four algorithms is shown in Figure 4.  
The results in Figure 4 indicate that as the cache capacity increases, the cache hit ratios of the GPA, NVCP, and CPOSCU algorithm improve by about 0.95%, 12.98%, and 19.36% compared to the LOCAL algorithm. But as the cache capacity continues to increase, the gap in the cache hit ratios between the four algorithms gradually decreases. On the one hand, when the probability of user requests being served by edge servers grows with the cache capacity, the cache service rate improves for the four algorithms; however, the cache capacity is limited, and the cache service rate gap becomes smaller when a certain value is reached. On the other hand, the LOCAL algorithm only considers the ratio of the cache space on the server; the NVCP algorithm caches the content with higher popularity at nodes with higher values, which reduces the update frequency, but it ignores the replacement rate of cache nodes and the value of cached content; the GPA algorithm considers the popularity of cached data, which improves the service rate of cache to some extent, but the CPOSCU is better than the GPA algorithm. The experimental results of four algorithms for data response time with varying storage capacities is given in Figure 5. The figure indicates that when the cache capacity is 50, the CPOSCU algorithm reduces the data response time by 14.43%, 10.37%, and 8.61% compared to the LOCAL, GPA, and NVCP algorithms. While the value of the cache capacity is 55, the data response time, respectively, decreases by 8.45%, 6.87%, and 5.41%. The point-fold line chart of the four algorithms on the number of replacements is outlined in Figure 6. When the values of cache capacity are 50 and 55, the CPOSCU algorithm improves by 8.33% and 1.86%, respectively, over the LOCAL algorithm; compared with the GPA algorithm, it improves by 26.95% and 8.14%; compared with the NVCP algorithm, it is, respectively, enhanced by 4.59% and 3.07%. This is mainly because the LOCAL, GPA, and NVCP algorithms are more effective than the GPA algorithm. Figure 4: Impact of cache capacity on cache service rate. Figure 5: Impact of cache capacity on data response time. and NVCP algorithms did not consider replacement costs, while the CPOSCU algorithm considers the replacement costs as placing data. Thus, the CPOSCU algorithm has the least number of replacements in a limited server space. 2. The impact of the different number of data blocks required on the algorithmic performance  
To evaluate the impact of different numbers of data blocks required on the algorithm's performance, the number of data blocks was set to vary in the range of 16-256. The cache service rate of the four algorithms with different numbers of data blocks is outlined in Figure 7.  
Figure 6: Impact of cache capacity on the number of replacements. Figure 7: Impact of different numbers of data blocks on cache service rate. As can be seen from Figure 7, the cache service rate of each algorithm gradually grows as the number of data blocks continues to increase. The cache service rate increases as the count of requested data blocks increases, allowing for more hits in the cache server. Among the four algorithms, the CPOSCU algorithm attains the highest cache service rate by considering the cache value of the cache object and the cost overhead of the edge server, which can ensure data persistence to some extent.