# A Novel Adaptive Cluster Based Routing Protocol for Energy-Harvesting Wireless Sensor Networks
## 2 Adaptive Hierarchical-Clustering-Based Routing Protocol for EH-WSNs
### HCEH-UC Routing Algorithm
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & **LEACH** & **LEACH-C** & **CEEC** & **HUCL** & **SEED** & **NEHCP** & **HCEH-UC** \\ \hline First node & 452 & 513 & 1000 & 1250 & 1510 & 1756 & 2535 \\ dead & & & & & & & \\ Half node & 534 & 555 & 1980 & 2510 & 3530 & 4100 & 4481 \\ dead & & & & & & & \\ Last node & 621 & 740 & 2675 & 3120 & 4200 & 4912 & 5145 \\ dead & & & & & & & \\ Average & 535.7 & 602.7 & 1885 & 2293.3 & 3080 & 3589.3 & 4053.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Lifetime metrics of the sensor node. Figure 3: Data transmission rounds before the first node dead (FND). ### Stability Period and Instability Period Evaluation

To conduct a more comprehensive comparison, the metrics of the stability period and instability period need to be evaluated. The protocol with a superior performance, including the CEEC, SEED, and NEHCP protocols, was chosen to obtain clearer figure results. The number of alive sensor nodes for these contrast algorithms was recorded in each round and is depicted in Figure 4.

Assume that the network with no exhausted nodes is defined as the stable phase, and the network with exhausted nodes is defined as the unstable phase. As shown in Figure 4, the proposed HCEH-UC possesses a longer stable phase. The LND of the network was also extended, which means that more data-transmission tasks can be executed. ### MLC Evaluation with Various Initial Energy

In order to perform the conventional routing protocol in various scenes, the energy levels would be set to 0.25 J, 0.5 J, 0.75 J, and 1 J in different scenes. The MLC of the conventional algorithms are depicted in Figure 5, and a quantitative comparison of the metrics is given in Table 5.

Figure 4: Number of alive sensor nodes per round for different routing protocols. Figure 5: MLC of different routing protocols under various energy levels. As shown in Figure 5 and Table 5, with the absence of energy harvesting, the MLC of the network would be prolonged, along with the increase in the initial node energy. Simultaneously, the proposed HCEH-UC has a superior performance at various energy levels compared with the contrast routing protocols. ### Relationship between Energy Consumption and Energy Harvesting

The network with limited energy capacity can be optimized using the proposed HCEH-UC. However, the monitoring function of the target area is finally invalid when a certain number of the nodes are exhausted. With the addition of the energy-harvesting technique, the proposed HCEH-UC can accomplish the uninterrupted coverage of the target area. The proposed HCEH-UC algorithm can adaptively adjust the distributed communication mode of clusters according to the topology relationship and the remaining energy of the cluster nodes. Thus, the working and sleep modes of the cluster head could be managed and the number of nodes in sleep mode can be controlled to accomplish energy harvesting. In order to demonstrate the effectiveness of the proposed HCEH-UC algorithm under the energy-harvesting condition, the remaining energy changes with the number of data-transmission rounds for one arbitrary cluster is shown in Figure 6, and the ordinate axis is set to a logarithmic axis in order to intuitively indicate the energy variation tendencies. Additionally, the energy consumption and collection situation of the nodes is depicted in Figure 6. Each energy collection and consumption cycle was divided into three stages, including the cluster head phase, data transmission to cluster head phase, and sleep and energy harvesting phase. When the residual energy is sufficient, the node alternatively acts as

Figure 6: Residual energy of the node with energy harvesting.