# Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Reschargeable Sensor Networks
## 6 Simulations and Results  
In this section, we evaluate the performance of ETS algorithm via simulations implemented by C++. To ensure the generality of the simulation results, we randomly generate a network as shown in Figure 3, and set the network parameters according to literature [39], as depicted in Table 1. The network includes 50 relay nodes randomly distributed, nearly half of them are selected as cluster heads of the corresponding clusters, which are not pictured out for clearness in Figure 3. Four wireless chargers are deployed uniformity in the target area, which are represented by red squares. Two nodes that can directly communicate with a wireless channel are linked with an imaginary line. Like many works such as [39; 41], a simplified model is considered in this paper for communications energy consumption in consideration of path losses. Both the free space (\(d^{2}\) power loss) and multipath fading (\(d^{4}\) power loss) channel models are employed, depending on the distance between the transmitter and receiver. Power control can be used to compensate for this loss. If the distance is less than a threshold \(d_{0}\), the free space model is used; otherwise, the multipath model is adopted. The performance is compared with the MTE algorithm, which has been enhanced for hybrid SDWRSNs. Figure 4 shows the tendency of energy consumption when the amount of SDN nodes increases. Obviously, the energy consumption of ETS algorithm declines with the increasing of SDN nodes and improve the energy efficiency for up to 20-40% comparing with MTE algorithm. This is because that more SDN nodes in the network can provide higher traffic scheduling ability to save more energy. Investigating Figure 4, we can find sometimes that the amount of increase of SDN nodes does not directly lead to reduction in energy consumption, e.g., from eight SDN nodes to 24 SDN nodes. There are three reasons for this phenomenon. Firstly, the new SDN node may not be the first SDN node on the MTE route of a flow and the ETS algorithm only schedules the flow at the first SDN node. Secondly, the new SDN node is the first SDN node on an MTE route, but there is only one optional path, and then there is no influence on the result. Thirdly, the new SDN node is the first SDN node and there are multiple optional paths, but the optional path chosen is the same as MTE route, which results in the same energy consumption as before. To show this tendency more clearly, we demonstrate the energy consumption in 100 periods when different amounts of SDN nodes are employed in Figure 5. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Network area & 400 m \(\times\) 400 m \\ Number of relay nodes & 50 \\ Period & 1 s \\ Data rate & \(1,000,000\) bits/s \\ Bit error rate & From \(1\times 10^{-5}\) to \(1\times 10^{-4}\), normally distributed \\ \(E_{elec}\) & 50 nJ/bit \\ \(\epsilon_{fs}\) & 10 pJ/bit/m\({}^{2}\) \\ \(P_{l}v\) & \(5\times 10^{7}\) nJ/s \\ Positions of wireless chargers & \((100,100),(100,300),(300,100),(300,300)\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The simulation parameters. Figure 3: Simulation network topology. Figure 6 shows the influence of network load on the energy consumption. We measure the energy consumption with the increasing of the amount of data produced by a subnet (or cluster) per period. The comparison is implemented among MTE and ETS with a different amount of SDN nodes. In the network with five SDN nodes, the energy consumption of ETS is slightly higher than that of MTE. This is because ETS will alleviate the load of wireless links that exceed the threshold \(\beta\), but MTE does not. Then, when the amount of SDN nodes grows, the ETS algorithm shows an increasingly larger advantage compared with the MTE algorithm. Figure 4: Energy consumption with different SDN nodes. Figure 5: Energy consumption increasing with time. Figures 7 and 8 show the latency of the MTE algorithm and ETS algorithm.