# An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments
## 5 Performance Evaluation
### Performance of ACxSIMv2  
ACxSIMv2 was simulated in eight different scenarios varying the \(THRESHOLD\) parameter values. As cited in Section 4.1, ACxSIMv2 uses \(THRESHOLD\) to control cluster formation based on the standard deviation of the nodes' measurements. In our previous work [20], we have used the following values: 0.1, 0.3, 0.5, 1.0, 2.0, 3.0, 4.0, and 5.0. However, since in ACxSIMv2 accepts \(THRESHOLD\) values for each dimension, we considered the values summarized in Table 3:  
Values close to 0 means no clustering, because there is no acceptable difference between measurements, and high values of \(THRESHOLD\) could lead to groups with high variance and, subsequently, the creation of virtual sensors not representative of the physical sensor nodes. Therefore, the measurements from these virtual sensors could not meet the users' interest. Figure 10 shows the energy consumption in \(mJ\) for each scenarios in both datasets. It is clear that there is a negative correlation between the \(THRESHOLD\) and \(Energy\) consumption variables, i.e., as the \(THRESHOLD\) value increases, the total energy consumption decreases. This is due to the fact \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenario** & **Temperature** & **Humidity** & **Light** \\ \hline
1 & 0.1 & 1.0 & 100 \\
2 & 0.3 & 1.5 & 150 \\
3 & 0.5 & 2.0 & 200 \\
4 & 1.0 & 2.5 & 250 \\
5 & 2.0 & 3.0 & 300 \\
6 & 3.0 & 3.5 & 350 \\
7 & 4.0 & 4.0 & 400 \\
8 & 5.0 & 5.0 & 500 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulated scenarios. Figure 9: 802.15.4 Data Frame  
that high values of \(THRESHOLD\) generate fewer clusters with more nodes in each cluster. Moreover, since ACxSIMv2 selects only a subset of sensor nodes from each cluster, there is a tendency of less nodes' activities (the total number of packets decreases). This behavior influences the overall energy consumption of the sensor cloud, since transmission is the activity the most draw current from the batteries in a sensor node [59]. Figure 11 depicts the percentage energy consumption savings with ACxSIMv2 compared to single-hop communication. As \(THRESHOLD\) value increases, the number of physical nodes per group also increases, causing a decrease in the number of groups. Since only a subset of nodes in each group responds, there is a decrease in the number of packet transmissions in the network, causing a reduction in energy consumption. However, although higher values of \(THRESHOLD\) seem to be the best configuration, because of the crescent energy savings, the MSE should be considered to properly select the \(THRESHOLD\) value. Since this parameter influences the similarity between the nodes' measurements in a cluster, the error (deviation) between real and transmitted data is also affected. Therefore, MSE is used to track how reliable are the measurements received by the middleware. To obtain the MSE, we have considered the the errors from the measurements of all dimensions. Figure 12 shows an increasing tendency in \(MSE\) as the value of \(THRESHOLD\) rises. As \(THRESHOLD\) represents the acceptable standard deviation in the cluster nodes' measurements, high values of \(THRESHOLD\) increase the error (deviation) in the MSE metric. Figures 13 and 14 reproduce the error between the real measurements from Intel Lab Node 18 and the measurements associated with its clusters (predicted data) during the simulations in the scenarios with \(THRESHOLD\) equals to 0.5 and 5. While in a cluster, Node 18 may be selected to transmit its measurements or could be put in a lower energy consumption state. Figure 13 points out that the predicted data closely follows the real sensed data. Most of the time, the error is within the limit of 0.5\({}^{\circ}\)C (with some occasional values up to 1.0). Similar results have also been observed for all the remaining nodes. However, in Figure 14, it is clear that the absolute error falls beyond 2\({}^{\circ}\)C in most of the time (with some occasional values up to 5).