# Joint Balanced Routing and Energy Harvesting Strategy for Maximizing Network Lifetime in WSNs
## 5 Simulation Results
better performance than the partial nodes charging approach for most of the other nodes in power consumption since it spends more operation cost for energy charging. For network lifecycle evaluation, the initial energy at each node is set to 0.6 J, and the network lifecycle is evaluated by operation rounds. The energy consumption per transmission bit is 50 nJ/bit and the data is 1000 bits in length [35]. The primary node with the highest power consumption rate is considered as the hotspot, which will limit the overall network lifecycle. Thus, the network lifecycle is inversely proportional to the highest power consumption rate of the hotspot. An additional model, called constant power charging rate is also designed in the energy harvesting scheme to achieve the everlasting WSNs. Figure 10 shows the network lifecycle of both SPT-EBR and Dijkstra algorithms. The power consumption scheme demonstrates an improvement of almost 52% over the Dijkstra scheme, and the power harvest scheme almost doubles the lifecycle than that of the Dijkstra scheme. In addition, the constant power charging rate can extend almost 6.5 times than the Dijkstra scheme in the overall network lifecycle. From the results, it can be concluded that the immortal WSNs can be achieved when the energy harvesting rate is greater than the power consumption rate, especially for the hotspot nodes. Figure 9: The power consumption rate distribution of the power harvest scheme in SPT-EBR. Figure 11 shows that the battery charging rate \(\Delta\)b of three cases includes the low, the medium and the high charging conditions for the worst hotspot node of packet transmission. The constant charging rate for the low case is 10 units/round, the medium case is 20 units /round, and the high case is 30 units/round. The high battery charging rate case achieves the best energy harvesting performance since the deployment cost is the highest. Because the parameter \(\Delta\)b is greater than 0 in the high charging rate case, it means that the battery of the worst sensing node is always in the positive charging state and will not be affected by the power consumption of packet transmission. In other words, the immortal WSNs can be achieved by control the positive charging rate for the worst hotspot node during packet transmission. In addition, the peak power consumption rate is 36/27/18/9 for the four intra-layers from the sink for the conventional scheme (blue curve) and is 23.2/11.9/6.9/3.9 for the SPT-EBR scheme in Figure 7, respectively. The peak power consumption rate means that the minimum charging power for each layer and thus the proposed method can save the charging power about 55.7% in average in each operation round. Figure 10: The network lifecycle of SPT-EBR and Dijkstra algorithms. Figure 12 shows the routing computation cost of power consumption scheme and energy harvesting scheme in the SPT-EBR and the Dijkstra algorithm. It can be observed that the Dijkstra algorithm achieves the least computation time to make the routing path convergence. To achieve lower power consumption rate and higher network lifecycle, the power consumption scheme spends additional 34% time cost for balanced routing computation. In the energy harvesting scheme, three strategies including the full nodes harvesting, the partial nodes harvesting and the constant harvesting achieve better network lifecycle extension but spends additional 72% time cost to generate the balanced routing paths. From the above results, it is better to spend routing computation cost in the early period rather than the late-remedy strategy in the maintenance phase to extend the network lifecycle. Figure 11: The battery charging rate of the worst hotspot node for SPT-EBR.