# Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks
## 3 Event Detection and Sensory Data Aggregation
Figure 6 shows the energy consumption when the transmission radius \(r\) is set to 0.1, 0.15, 0.2 or 0.25, respectively. The other parameters are the same as those in Figure 2. Similar to \"number of relay nodes\" in Figure 2, \"energy consumption (KJ)\" in Figure 6 specifies the energy consumed in total for all relay nodes in these 10, 20 or 30 time slots. Figure 6 shows that the energy consumption decreases when \(r\) is set to a relatively large value. This is due to the fact that the number of relay data packets decreases when \(r\) increases. As indicated by the values in Table 1, the smaller the number of data (or control) packets is to be transmitted, the less the energy is to be consumed. As presented

Figure 5: Comparison of the number of relay data packets when the transmission radius \(r\) is set to various values. This figure shows that the number of relay data packets declines when the transmission radius is set to a relatively large value. by Figure 5, when \(r\) is large enough, the number of relay data packets is almost steady. Therefore, the energy consumption may not decrease to an extent. It is worth mentioning that when \(r\) is large, there may exist relay nodes that may relay sensory data for a single sensor node. This may induce an imbalance of energy consumption between relay sensor nodes and may be harmful to the network lifetime. Consequently, a tradeoff should be considered when setting a value for \(r\) in real applications. Figure 7 shows the energy consumption when the number of sensor nodes, which drift with the water dynamics and change their coordinates, is set to 10, 20, 30, 40 or 50, respectively, where the \(x\)- and \(y\)-coordinates of these sensor nodes change no more than 3-5 m and their \(z\)-coordinate changes no more than 0-3 m, per time slot. The energy consumption is the amount in total for the experiments conducted for 20 time slots. The other parameters are set to the same values as those in Figure 2. As presented by Algorithm 2, the larger the number of sensor nodes whose coordinates change is, the larger the number of relay nodes that have to be re-selected and the larger the number of \(HeartB_{tet}\)-EPONG control packets to be transmitted. Therefore, more energy is to be consumed during the relay nodere-selection phase, as shown in Figure 7. This figure indicates that our technique is more energy efficient when the network topology is relatively steady. Figure 8 shows the number of sensory data packets that a certain relay node delivers, when sensor nodes are deployed in the network space under various skewness distributions. Intuitively,

Figure 2:0 Comparison of energy consumption when the transmission radius \(r\) is set to various values. Generally, the larger the value of \(r\) is, the less the energy consumption is for sensory data gathering and routing to \(SN\). Figure 2:1 Comparison of energy consumption when the number of sensor nodes, which drift with the water dynamics and change their coordinates, is set to various values. This figure shows that the larger the number of sensor nodes changing their coordinates, the more energy is to be consumed. two sensor nodes (denoted \(uv_{1}\) and \(uv_{2}\)) can have a link, when the geographical distance \(dst\) between \(uv_{1}\) and \(uv_{2}\) is shorter than the communication radius \(r\). Given the set \(dst\)], the variance is adopted to represent the skewness degree of the sensor node distribution. Generally, when the variance is smaller, which means that the geographical distances between sensor nodes are more similar, sensor nodes are distributed more evenly in the network region. In our experiments, three kinds of sensor node distributions have been generated and their variances are 60 km, 80 km or 100 km, respectively.