# Caching Placement Optimization Strategy Based on Comprehensive Utility in Edge Computing
## 5 Experiment and Analysis
### Experimental Results and Analysis
The performance comparison experimental results of data response time among the four algorithms under the range of required data block numbers is demonstrated in Figure 8. The data response time of each algorithm rises with the increasing number of required data blocks, while the data response time of the CPOSCU algorithm is the lowest and the data response time of the LOCAL algorithm is the highest. Owing to this, the LOCAL algorithm prioritizes placing data with a high cache value on servers with a low replacement rate, but the CPOSCU algorithm effectively improves the data hit rates while also ensuring data stability. The impact of replacement numbers under the range of required data block numbers is illustrated in Figure 9. The replacement rates of the four algorithms increase as the quantity of the required data blocks increases. However, when the quantity of required data blocks is small, the difference in the number of replacements between the CPOSCU algorithm and the LOCAL algorithm is not much different, mainly because the LOCAL algorithm considers the cache ratio of available space, and the CPOSCU algorithm also considers the cache space and replacement cost; however, when the number of data blocks is large, the CPOSCU algorithm has the lowest replacement number. Figure 5.0 Impact of different numbers of data blocks on data response time. 3. The Impact of different data block popularities on the algorithmic performance  
To evaluate the impact of different data block popularities on the algorithmic performance, the range of data block popularity variation was set from 0.7 to 1.2. The variation process of the cache service rate with data block popularity is reflected in Figure 5.1  
As can be seen from Figure 10, the LOCAL algorithm has the lowest cache service rate, while the NVCP algorithm is higher, and the CPOSCU algorithm has the highest cache service rate. This is mainly because the LOCAL algorithm only considers the cache space ratio; the NVCP algorithm caches data having a higher popularity to nodes with higher values, ensuring data diversity, but the replacement cost of edge servers is ignored. The CPOSCU algorithm guarantees the stability of the data cache in the edge server by accounting for the cost overhead along with the cache value of the data blocks. The impact of data response time on the number of data blocks is illustrated in Figure 5.2 This is primarily caused by the fact that the data response time decreases as the  
Figure 5.3 Impact of data block prevalence on cache service rate. Figure 5.4 Impact of different number of data blocks on the number of replacements. probability of a user hit increases with the increasing popularity of the data block. Furthermore, it is clear that the CPOSCU algorithm has the lowest and the LOCAL algorithm has the highest data response time. The reason is that the LOCAL algorithm is a random cache, while the CPOSCU algorithm considers the replacement rate and cost overhead of the edge server as well as the data block's prevalence. The effect of replacement numbers under the different data block's popularity is illustrated in Figure 5.5 The LOCAL algorithm keeps the number of permutations stable as the popularity increases, while the GPA, NVCP, and CPOSCU algorithms decrease most significantly. This is because the LOCAL algorithm only performs random caching and has the largest number of permutations; other algorithms take into account the data popularization, which generates a reduced number of permutations, while the CPOSCU algorithm considers the server permutation rate in addition to the prevalence. Therefore, it generates the smallest number of permutations. Figure 5.6 Impact of data block prevalence on data response time. Figure 5.7 Impact of data block prevalence on the number of replacements.