# An Energy Efficient Sink Location Service for Continuous Objects in Wireless Sensor Networks
## 4 Performance Evaluation
### Total Energy Consumption  
Figure 15 left shows the cumulative energy consumption. In TTDD, each cluster head constructs grid structure respectively. TTDD consumes little energy at early of simulation because a few sources detect the continuous object and a few cluster heads is elected. However, the energy consumption greatly increase by the time since the number of sources increases. On the other hands, the energy consumption of LBDD and OCOT much less than in case of TTDD because LBDD and OCOT construct one structure regardless of the number of sources. Though LBDD consumes much less energy, the energy consumption of LBDD draws a slow and exponentially rising curve because the reported data from cluster heads are shared into receiving \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Values** \\ \hline Network size and \# of sensor nodes & 500 m \(\times\) 500 m and 1000 nodes \\ Transmission range & Omnidirectional 20 m \\ Transmitting/receiving power consumption rates & 20 mW /15 mW \\ Frequency of location update and data report & Every 5 s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Default simulation environment settings. Figure 14: Tracking scenario. group of inline-nodes. The sharing overhead increases as the number of report increases. OCOT consumes more energy than others at early of simulation since the overhead for constructing a grid structure and clusters at whole network while TTDD and LBDD consume small energy for simple grid structure and line structure construction respectively. However, OCOT consumes much less energy at later of simulation because integrated location update and direct data report. The individual location update of TTDD and LBDD consume much more energy. Figure 15 right shows the total energy consumption according to the number of sensor nodes. In this simulation, we vary the number of sensor nodes from 800 to 1400. The number of sensor nodes means the average density of nodes per unit area because the network size is unchanged. We adopt simple method for selecting boundary nodes so the number of boundary nodes increases as the node density of nodes increases. The total energy consumption of TTDD rises sharply and it means that TTDD is heavily influenced by the number of nodes because of the grid structure construction overhead being proportional to the number of boundary nodes. The total energy consumption of LBDD increases slowly and it is caused by the data sharing overhead of inline-nodes while the energy for constructing line structure is not affected by the number of nodes. This shows that the grid construction overhead in TTDD is more influenced by the number of boundary nodes than the data sharing overhead in LBDD. On the other hand, OCOT is barely affected by the number of boundary nodes. Actually, the location update overhead of OCOT increases as the number of boundary nodes increases but it is relatively low compared to either the grid construction in TTDD or data sharing overhead in LBDD. Figure 16 left shows the total energy consumption when the diffusion speed of the continuous object is 0.5, 1.0, 1.5, and 2.0m/s. A continuous object diffusing at high speed might occupy larger area than one diffusing at low speed at same time. Namely, the diffusion speed influence the growth rate of the number of sources. Figure 16 left is similar in the tendency to Figure 15 right. The total energy consumption of TTDD more sharply increases than others and the total energy consumption of LBDD is relatively higher than that of OCOT. The difference is shown in Figure 15 right when the diffusion speed is 2. Commonly, the gradients of each graph slightly decrease. It caused by the size of the network and the location of the origin node in the simulation setting. When the diffusion speed is less than 1.5, the perimeter of the continuous object is within the network. However, in case of the speed is 2, the perimeter increases over the network since the radius of the continuous object passes over the boundary of the network.