# Text Semantics-Driven Data Classification Storage Optimization
## 4 The Related Energy and Cost Model
### Energy Consumption Model  
As the storage system adjusts the performance modes of disks based on seasonal variations, the total energy consumed within one year is the total energy consumption over the four seasons. \[E_{total}=E_{total\_spring}+E_{total\_summer}+E_{total\_autumn}+E_{total\_ winter}\]  
Given space limitations, we employ the spring as an illustrative example. Throughout a specific spring month, disks in both the spring and without seasonal feature storage areas \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Explanations** \\ \hline \(D\) & Entire capacity \\ \hline \(n\) & Total disks \\ \hline \(E\) & Energy consumption \\ \hline \(t_{total\_idle}\) & The idle status time’s proportion over a year \\ \hline \(v^{h},v^{l}\) & The transfer rate in two modes \\ \hline \(n_{s},n_{m},n_{a},n_{w}\) & The quantity of disks within the seasonal storage area \\ \hline \(D_{season}\) & The data capacity within each seasonal storage area (e.g., \(D_{spring}\)) \\ \hline \(\eta_{season\_active}^{h}\) & The percentage of disks in high mode with active status within each \\ seasonal storage area (e.g., \(\eta_{spring\_active}^{h}\)) \\ \hline \(\eta_{season\_active}^{l}\) & The percentage of disks in low mode with active status within each \\ seasonal storage (e.g., \(\eta_{spring\_active}^{l}\)) \\ \hline \(t_{season\_idle}\) & The time that disks spend in idle status within each seasonal storage area \\ (e.g., \(t_{spring\_idle}\)) \\ \hline \(\delta_{season\_active}^{h}\) & The proportion of data volume in high mode in active status within each \\ seasonal storage area (e.g., \(\delta_{spring\_active}^{h}\)) \\ \hline \(\delta_{season\_active}^{l}\) & The proportion of data volume in low mode in active status within each \\ seasonal storage area (e.g., \(\delta_{spring\_active}^{l}\)) \\ \hline \(p^{h},p^{l}\) & The cost associated with processing data under two modes \\ \hline \(p^{h}\) & Data storage cost \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters and explanations needed to design the model. run in high-performance mode, with the remaining disks assigned to low-performance mode. The energy consumption is evaluated as follows: First, the count of disks in active status within the spring storage area is \(n_{s}\times\eta_{spring\_active}^{h}\). The overall transfer speed is \(v^{h}\times n_{s}\times\eta_{spring\_active}^{h}\). Then, the data volume of spring active status is \(D_{spring}\times\delta_{spring\_active}^{h}\). Next, we derive the time spent in transmitting these data as \(\frac{D_{spring}\times\delta_{spring\_active}^{h}}{v^{h}\times n_{s}\times\eta _{spring\_active}^{h}}\). Finally, during active status, the spring energy consumption in high-performance mode is represented as \(\frac{E_{a}^{h}\times D_{spring}\times\delta_{spring\_active}^{h}}{v^{h}\times n _{s}\times\eta_{spring\_active}^{h}}\). The variable \(T\) represents the operational time of a storage system over one year. During the spring season, the cumulative operational time is \(\frac{T}{4}\). The expression for the ratio of the total idle time in spring to the total operational time during spring is given by \(t_{spring\_idle}\). We calculate the spring energy consumption during idle status as \(E_{i}^{h}\times\frac{T}{4}\times t_{spring\_idle}\). By analogy, we can obtain the other seasons' energy consumption.