# Automated Methodology for Dependability Evaluation of Wireless Visual Sensor Networks
## 5 Results and Discussion
### Example 2  
This example set up a larger system in order to analyze the effects of routing protocols strategies, links and battery discharges upon the availability evaluation. In addition, the availability with respect to parameters' variation (failure and repair rates) is analyzed. For this purpose, we consider the WVSN represented in Figure 13, with five visual nodes, four scalar nodes and one sink node. The monitored area has \(18\times 10^{4}\) m\({}^{2}\) and the minimum required coverage area is 20%, which is \(\lambda_{min}=36\times 10^{3}\) m\({}^{2}\). This implies the following network failure condition:  
\[\begin{array}{l}\text{NFC}=(V1\wedge V3)\vee(V1\wedge V5)\vee(V1\wedge V7) \vee(V1\wedge V9)\vee(V3\wedge V5)\vee\\ \vee(V3\wedge V7)\vee(V3\wedge V9)\vee(V5\wedge V7)\vee(V5\wedge V9)\vee(V7 \wedge V9),\end{array} \tag{9}\]  
where operator \"\(\wedge\)\" indicates an AND gate and operator \"\(\vee\)\" indicates an OR gate. The hardware and link failure rates are \(\lambda_{hw}=1.1416\times 10^{4}/\text{h}\) and \(\lambda_{lk}=0.0417/\text{h}\), respectively, which means one hardware failure per year and one link failure per day, and hardware and link repair rates of \(\mu_{hw}=0.0208/\text{h}\) and \(\mu_{lk}=2/\text{h}\), respectively, which means one day to repair the hardware and 30 min to reestablish a link.  
Figure 12: Graphical methodology output.  
Figure 13: Area coverage in Example 2.  
First, we analyzed the effect of the routing protocols' strategies. Figure 14 shows the network topology for DIRECT and FLOODING strategies. Figure 15 shows the availability evaluation of those topologies. As it was expected, the FLOODING strategy presents higher availability (\(\approx\)94%) then the DIRECT strategy (\(\approx\)92%) due to the fact that there are multiple possibilities to reach the sink. This is an interesting result because, besides providing a higher availability, FLOODING strategy also allows each visual node to reduce its radio transmission power and therefore to save battery. However, this methodology is not able to measure such power consumption savings yet. For this purpose, the battery modeling should be directly integrated into the routing protocol, in order to associate the average discharging current according to the selected routing strategy. This task could be performed by simulation, which is out of the scope of this work.  
We also analyzed the effects of link and battery failures upon the system availability, using each of the routing strategies. To cope with this analysis, the system availability is evaluated in four different ways: (i) considering only hardware failures to provide a comparison basis; (ii) considering hardware and link failures to highlight just the link failure effects; (iii) considering hardware and battery failures to highlight just the battery failure effects; and (iv) considering hardware, link and battery failures together to obtain the overall system behavior. Figure 16 plots the result of these analysis based on DIRECT strategy and Figure 17 based on FLOODING strategy.  
Figure 14: Network topology of routing strategies (**a**) DIRECT and (**b**) FLOODING.  
Figure 15: Availability of the network of Figure 13.  
From Figures 16 and 17, it is possible to notice that the battery discharge is the component that causes a major effect upon the system availability, since the battery discharges faster than the other failures' occurrences. On the other hand, link failures have a smaller impact due to their transient behavior, which strongly depends on the routing protocol. Notice that link failures barely interfere in a network with FLOODING strategy, while it presents a considerable effect upon a network with DIRECT strategy. This is due to the fact that, in a network with FLOODING strategy, a lost path is quickly replaced by another one.