## 4 Experimental Validation and Result Analysis
### Comparative Analysis of Retrieval Speed  
This paper introduces a data storage model based on multi-level time encoding. Based on the stored time coding in the column family, the initial storage model allows retrieval of all taxi trajectory point data within the same period. However, the time coding cannot serve as the row key of the data table to establish a unique index for more efficient retrieval of all taxi trajectory point data within the same period. Consequently, the original storage model presents limitations in this particular usage scenario. Thus, this experiment refines the storage structure of the original data storage model in harmony with practical application to enhance the retrieval efficiency of the storage model within this specific scenario.  
To ascertain the enhanced retrieval efficiency of the improved data storage model, this paper conducts retrieval speed tests on both the enhanced and original models using different periods (minutes, hours, days) as the unit. Each test is repeated 100 times to calculate the average retrieval speed for each storage model. The results are depicted in the bar chart shown in Figure 6, indicating that the improved model outperforms the original model in retrieval speed. Furthermore, from the line graph in Figure 6, the following observations can be made: when extracting data in minutes, the retrieval speed of the improved storage model is 6.206 times faster than that of the original storage model; when extracting data in hours, the retrieval speed of the improved storage model is 12.475 times faster than that of the actual storage model; and when extracting data in days, the retrieval speed of the improved storage model is 18.634 times faster than the original storage model. Hence, as the volume of retrieved data continues to increases, the retrieval efficiency of this storage model becomes increasingly superior to that of the actual storage model.  
Similarly, this paper conducted retrieval speed tests on the improved and space-time-coded storage models [19]. The experimental results are shown in Figure 7. When extracting data in minutes, the retrieval speed of the improved storage model is 1.151 times faster than that of the space-time-coded storage model; when extracting data in hours, the retrieval speed of the improved storage model is 1.585 times faster than that of the space-time-coded storage model; and when extracting data in days, the retrieval speed of the improved storage model is 1.962 times faster than the space-time-coded storage model. The results prove that, when retrieving data based on time information as a query condition, the improved storage model exhibits higher retrieval efficiency than the space-time-coded storage model. This is because utilizing time encoding allows for the rapid localization and extraction of data within a specified time range. In contrast, space-time coding considers  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Eps** & **Minpts** & **Silhouette Coefficient** \\ \hline
0.0016 & 62 & 0.814642156 \\
0.0017 & 64 & 0.754129534 \\
0.0018 & 63 & 0.765243894 \\
0.0019 & 62 & 0.814536452 \\
0.0020 & 62 & 0.824153594 \\
0.0021 &  
spatial and time information, requiring a more complex calculation process during queries, which, to some extent, reduces retrieval efficiency. Therefore, time encoding is more direct and efficient in such a usage scenario.