# Energy-Efficient Resource Provisioning Strategy for Reduced Power Consumption in Edge Computing +
## 6 Simulation and Results
### Simulation for the Resource Provisioning Strategy  
In this section, we conduct our experiments on the iFogSim simulator platform [27]. iFogSim is a popular simulator in the area of edge computing which implements many features of the edge architecture, such as the edge network structure, the placement of task modules, and the task system. In our simulation, we realize our scheduling strategy and modify the power consumption model to adapt the sleep power consumption mode based on the iFogSim simulator. We assume that each sensor is equipped with a set of edge nodes for receiving tasks. In our simulation, 24 edge nodes are used which divided into 4 groups. The detailed configuration of the simulator is shown in Table 4. For each group, we set six edge nodes that connect to the upper-level cloud through a gateway and a proxy server. We first performed the scheduling strategy under the master-slave mode and non-master-slave mode. The experimental result is shown in Figure 6. The abscissa is the name of the device under a gateway in the architecture, and the ordinate is the power consumption of the edge nodes in this experiment. According to the result, we find that the power consumption has a certain fluctuation due to the normal distribution, but the mean value is still very stable which means that the power consumption of each node is similar. Thus, we have that the total number of tasks that the edge nodes process is similar which is not affected by the dynamic generation. As shown in Figure 7, we experiment with different mission generation densities. The horizontal axis is the value of the mean in the normal distribution for each task, and the vertical axis is the total power consumption of the edge nodes in this experiment. The experimental results show that with a mean of 5, the power consumption of the non-master-slave is 3.3% lower than that of the  
Figure 5: Total delay of the users. Figure 6: Power consumption of five edge nodes in a gateway. master-slave. In the experiment with a mean of 6, the power consumption dropped by 18.5%. In the experiment with a mean of 7, the power consumption dropped by 26.3%. In the experiment with a mean of 8, the power consumption dropped by 27.9%. It can be concluded that with the intensive task generation, the advantages of the strategy under the master-slave mode are getting smaller and smaller. The algorithm proposed in this paper has obvious optimization of the power consumption when the task density is small. When the task density is large, the power consumption under both modes is nearly the same. As shown in Figure 8, we calculate the delay of two scenarios under different task volumes. The horizontal axis is the value of the mean in a normal distribution for each task, and the vertical axis is the mean of all task delays in this experiment. The experimental results show that in the experiment with a mean of 5, the delay of non-master-slave is 0.04% higher than the delay of master-slave. In the experiment with the means of 6 and 7, the delays increased by 5.25% and 16.69%, respectively. Similarly, the delay increased by 17.07% with a mean of 8. The algorithm proposed in this paper has certain side effects on delay, but in different groups of experiments, the power consumption savings ratio is greater than the delay increase ratio. According to the experimental results above, we make the following conjectures. Assuming that a task is a minimum migration unit, we cannot place a task on two devices in parallel. Since the task is indivisible, in the case where the total computing power of the master-slave mode and the non-master-slave mode is the same. When there is no task to be processed, we can see that the power consumption under the master-slave mode is much lower than the non-master-slave mode. When there is only one task to be processed, the slave node must be in a sleep mode under the master-slave mode. The computing capacity under the non-master-slave mode is significantly stronger than the master-slave mode.