# An Efficient Location Verification Scheme for Static Wireless Sensor Networks
## 6 Performance Evaluation  
The purpose of the evaluation is to verify the relationship between the variables proposed in Equation 5. The performance of the MSRLV was evaluated using the C++ language. The simulation results in this section, which are in accordance with the hypothesis presented in Section 5.1, can support the validity of our simulation. As before, the sensors are deployed in a 300 m \(\times\) 300 m square area. The position of sensors is determined based on the grid deployment strategy or the uniform random deployment. The grid deployment strategy is selected because the proposed verification is expected to perform the best when sensors are evenly deployed at a fixed distance. The test results under the grid deployment can be used to understand the performance under the uniform random deployment, which is a widely-used deployment strategy in the WSN. Each of the deployment strategy examples with some attackers is shown in Figure 13. Note that the evaluation in this paper is performed against two relatively stable deployment scenarios, such as grid and uniform, but it is expected to work in other deployment scenarios, such as a Gaussian distribution, if the network density is high enough. However, the proposed scheme may not work well when the network density becomes lower, i.e., at the edge of the network in the Gaussian deployment scenario. The communication range of sensors is 20 m based on the choices made in prior studies [11; 15], though in the real world, the underlying standard of these sensors, IEEE 802.15.4, can support a range of up to 100 m.  
The simulation does not consider the physical, MAC, routing layer functions of wireless sensor networks. If sensors can acquire the neighbor information reliably, any existing MAC and routing \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sensor Product** & **RAM (KB)** & **Storage (KB)** & **Maximum Memory Consumption (B)** \\ \hline \hline \multicolumn{1}{c}{Btnode 3} & 64 + 180 & 4 & 340 \\ mica2 & 4 & 512 & 340 \\ mica2 dot & 4 & 512 & 340 \\ micaz & 4 & 512 & 340 \\ telos A & 2 & 256 & 340 \\ tmote sky & 10 & 1024 & 340 \\ EYES & 2 & 4 & 340 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Memory size of each sensor product and memory consumption for the proposed scheme. Figure 13: Deployment strategy of sensors in the target zone with 1000 sensors. Ten percent of them are smart attackers, and each attacker fakes its location by about 10 degrees. protocol can be used as the underlying protocol. In the simulation, the communication channels are assumed to be bidirectional between sensors. This means that sensors i and j can hear each other when they are within each other's communication range. The asymmetric links are common in wireless networks and caused by physical issues, such as multipath fading or shadowing, but techniques, such as a handshaking, a proper coding scheme [27] or channel hopping [28], can be used to overcome the asymmetry of the links. By adopting those techniques, sensors can find and use the stable communication range while setting up the network, so that the sensors can gather the neighbor information reliably. However, one should note that the performance of the MSRLV will be decreased when the MSRLV is applied to the real-world application because the signal interference can be easily caused by obstacles in the real-world environment, and this cannot be completely eliminated by those mitigation methods. The simulation was run according to the simulation parameters shown in Table 5. Each sensor in the network performed location verification on each of its neighbors. The total number of sensors in the network varied between 100 and 1000 by increments of 100, so that each sensor had its neighbors between zero and 13. Malicious sensors accounted for 10% of the total. There were two types of attackers: smart and dumb. Dumb attackers claimed that they had a location chosen at random between 10 m and 20 m away from their real locations in any direction without considering which sensors would act as their verifiers.