# Data Access Based on a Guide Map of the Underwater Wireless Sensor Network
## 6 Experiments and Analysis
### Experiment Results and Comparative Analysis
The best of time performance is in State 2, because of its data transmission with fewer hops. However, because of the large communication distance, energy consumption is also the greatest. If there is no application data that meets the query sentence in the network, there is no data storage. In the process of data query, there is also no transmission of the specific application data. The results of the experiment performance are as shown in Figure 7.  
From the experimental results, we can draw the following conclusions:  
1. When it comes to the query time, the value of performance indexes on GHT do not change compared with Figure 6, because the query data processing is not changed in Scenario 1. In this case, all storage nodes must be checked out, and then the result that the network has no application data will be given. Thus, the query time does not change in GHT. In DAGM, if the center ring node does not find the content abstracts and storage location abstracts of the data that form query sentence through the metadata, it directly returns the result of _query failed_. Therefore, the data query time becomes much shorter (shown on the left side of Figure 7a, from 108 s to 12 s in state 1). 2. When it comes to energy consumption, in DAGM, there are no the routing and specific data requests sent to data storage node, and there are also no specific application data transmitted to the user. Therefore, the energy consumption of the network is of decreased amplitude (in state 1, shown in right side Figure 6b,c and Figure 7, global query and partial query drops from 578 J to 144 J). In GHT, the energy consumption of the network does not decline. 3. In three different states, the minimum change trend of the time performance and total energy consumption is similar in Scenario 1. Figure 6: The experiment results where application data exists in the network. (**a**) The performance in storage. DAGM: data access based on a guide map; GHT: geographic harsh tables; (**b**) The performance in global query; (**c**) The performance in partial query. After the above experiment, we set the sensor's communication radius as \(r_{b}\) = 10 km, the number of deployed sensors as \(n_{b}\) = 400, and the average connectivity degree as \(k_{b}\) = 8.5. Based on sensor nodes uniform deployed in 80 km \(\times\) 80 km (Setup 1) underwater region, we change the network deployment region size, which is respectively 100 km \(\times\) 100 km (Setup 2) and 120 km \(\times\) 120 km (Setup 3), and then experiments have been conducted for comparing the performance of our DAGM and QPM[20](2015). In QPM, a routing tree is constructed where a sensor node corresponds to a tree node, and A sensor node acknowledges the fact that whether it lies within the sub-region of interest or not. Sensory data are routed to the sink node leveraging the parent-child relation of sensor nodes specified in the routing tree. So the QPM complements the querying data function which interest in partial, rather than the whole, network region. In the experiment, the routing protocol data and sensory data transmission mechanism were adopted in our technique, and the calculation of energy consumption on data delivery was also adopted in our approach. The experimental results are shown in Figure 8.  
As seen in the experimental results shown in Figure 8, when it comes to data storage time and data query time, for DAGM and QPM in Setup 1, Setup 2 and Setup 3, the node deployment in the network just increases the distance between nodes, and then the communication time between nodes increases, so the data storage time and query time increase linearly. However, the energy consumption of the network becomes dramatically larger with the distance between sensor nodes becoming larger, which is mainly due to the cubic relationship between energy consumption and the communication distance. From this perspective, the method of this paper is in line with the general facts. Figure 7: The experimental results where the network does not have application data.