# Text Semantics-Driven Data Classification Storage Optimization
## 5 Experiments and Evaluation
### Results and Discussions
#### 5.2.2 Comparison Across Multiple Disk Models  
To emphasize the benefits of the semantic similarity method, we expand our analysis to different disk models. The energy consumption of these strategies on three different disk models in the year 2020 is shown in Figure 6. Notably, the semantic similarity approach maintains its advantageous position under the HUC109090 CSS600 disk model, while presenting an unstable trend under the other two disk models. It can be seen that the selection of disk models has a certain impact on the energy consumption reduction effect of data classification storage schemes. Through analysis, we find that the average rotation latency is a crucial parameter affecting energy consumption simulation. Compared with HUC109090 CSS600, the other two models have a significant gap in average rotation delay parameters, even up to twice. This plays a crucial role in the increase in energy consumption. In other words, the negative impact of the average rotation latency offsets the positive benefits brought by the classification storage scheme.  
The comparison of total operating costs of different disk models is presented in Figure 7. Remarkably, regardless of the specific disk model, the total operating cost of AS-H is always the highest, while the semantic similarity method consistently registers the lowest. A detailed comparison reveals that, in comparison to AS-H and K-ear, the semantic similarity method achieves substantial operating cost savings in different disk models, ranging from 11.77% to 19.15%, 13.75% to 22.03%, and 12.78% to 21.42%, respectively. By analyzing the parameters of the three disk models, it can be found that compared to HUC109090 CSS600, the other two models did not have a significant gap in data processing costs. This means that the negative impact of the increased costs is smaller than the positive benefits of data classification storage approaches.  
Figure 5: Annual total operating cost of different methods (2018–2020). We compare the operating costs of all approaches through the cost module designed by us in CloudSimDisk. Compared to AH-S and K-ear, the semantic similarity method economizes operating cost by up to 13.20–22.17%.  
In the thorough analysis of overall energy consumption and total operating expenses, we can obtain two key conclusions. Firstly, the semantic similarity method consistently outperforms the other two strategies across different periods, highlighting its edge in overall power consumption and operating cost. Secondly, while the superior performance in energy consumption may exhibit some variability under different disk models, the  
Figure 6: Total energy consumption of different disk models. The energy consumption of the semantic similarity method is always lower than that of K-ear. AS-H is greatly affected by disk performance.  
Figure 7: Total operating cost of different disk models. For all disk models, the energy consumption of the semantic similarity method is always lower than those of AS-H and K-ear. AS-H has the highest operating cost.  
semantic similarity method consistently maintains stability in terms of operating cost. In implementing the semantic similarity approach, it is necessary to pair it with high-performance disks to fully leverage its advantages. Otherwise, the benefits brought by data classification approaches may be masked by the negative impact of the disk.