# A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks
## 6 Analysis and Conclusion  
The clustering algorithm commonly used in wireless sensor networks balances network energy and extends system operating time. However, intra-cluster communication and data forwarding between cluster heads cannot use the overall energy optimal path, which makes the energy of the whole system waste a lot. The power line connection method proposed in this paper fully balances the energy between nodes, so that all nodes can transmit data with the energy optimal path, saving the overall energy and significantly improving the system lifetime. Although the power cable is added to the system, it is essentially different from the traditional wired data transmission system. In the wired data transmission system, the communication cable used for data transmission is very strict. To ensure stable and reliable communication, the cable impedance is required to be uniform and must be able to resist signal interference. In larger sensor systems, the large number of communication cables required for wired transmission makes the system expensive and difficult to deploy. In the form of wired communication, data can only be transmitted between nodes connecting cables, reducing communication flexibility. The power line is only the DC power supply between the connected nodes, and does not require the cable to have communication capability, the cost is low, and the deployment is relatively easy. In a complex field environment, cable disconnection may occur. If wireless communication is used, system data transmission will not be affected. A small number of power lines are disconnected to divide the entire connected system into several small connected systems, and the energy in each small system is still balanced. It can be seen from the simulation results that the power conversion scheme of connecting the sensor nodes with the power line extends the working time of the wireless sensor network by more than four times. Most importantly, our proposal makes all nodes work longer. This is critical to systems that work together as a whole, ensuring that data is reliable and complete. In addition, in IoT (Internet of Things) applications, the energy of sensor nodes is the key to system performance [30; 31]. Our proposal ensures that there is a continuous supply of power to key nodes in the IoT application, keeping the IoT system in high performance. Many wireless sensor networks collect renewable energy sources which are unevenly distributed. For example, solar energy, only nodes with sufficient light can collect enough energy, and the nodes placed in the shadows have no energy supplement. The scheme of connecting the power line can transfer energy from the sun-irradiated area to the shaded area, making full use of the energy collected by all nodes and making better use of renewable energy to extend the lifetime of the system. Of course, the price paid is that a power line is connected between the nodes. This undoubtedly increases the system cost, which is mainly the cable cost and installation cost. Regarding the cable cost, a rough value can be calculated according to Equation (7). Power cables are inexpensive, but sensor prices vary widely. The ratio of the power cable cost to the total cost of the original wireless system is \(r\)  
\[r=\frac{\text{W}}{P_{sensor}}=\frac{L\times P_{cable}}{P_{sensor}}, \tag{11}\]  
In the Formula (11), \(P_{sensor}\) is the price of a single sensor node. For some expensive sensors, \(r\) is small; for low-cost sensors, this ratio is considerable. For example, if a sensor system deploys 400 sensor nodes in a 100 m \(\times\) 100 m area, then \(L\) = 5 m. We assume that the price of the power cable is about 15 per meter, and the price of the sensor node is 1005 per unit. According to Equation (11), the cost of the power line connection scheme is increased by 5%. According to the simulation results of Figure 9, the system lifetime can be extended by about 2.3 times in this situation. Costs should be calculated based on cable and sensor prices in different applications.