# Secure and Time-Aware Communication of Wireless Sensors Monitoring Overhead Transmission Lines
## 3 Transmission Line Monitoring Using WSN in Smart Grids
### Smart Grid Architecture
In order to fulfill their role accurately, transmission line monitoring systems need to have continuously updated information on measured parameters. As a consequence, proper synchronization between wireless sensors is required, so that the quantities measured in different points of the transmission line could be directly comparable. Implemented WSN monitoring system must be able to acquire information on different nodes of a network in a synchronized manner and distribute the data. Given the complexity of the system to which is applied, the problem of measurements synchronization is an enormous challenge in and of itself. The synchronization accuracy requirements can significantly change depending on the constraints of the applications which vary from system to system. In environmental monitoring applications there exist several possible synchronization solutions. One of the available approaches is to use time stamps, which can be further compared and analyzed. However, in practice, with Network Time Protocol (NTP)-based solutions it is sometimes difficult to ensure such mechanisms are in use and correctly configured on all sensors. Another possible approach is to use the so-called trigger signal for synchronous triggering of each measurement. With such an external synchronization, the system under test triggers a synchronization signal. This method allows to assess the measurement system response with a great accuracy. In the proposed scenarios, we simply assumed that the measurements are triggered by the synchronization signal, such that they are made at the same time, and further transmitted to the substation with the help of the chosen routing algorithm. Designing our scenarios, we assumed that a power line is located in an open area, where relay nodes antennas are rather visible for each other. However, since wireless radio channel puts fundamental limitations to the performance of wireless communications systems (radio channels are extremely random, and are not easily analyzed), modeling the radio channel is typically done in statistical fashion, using mathematical transmission models. Because the path loss is the largest and most varied quantity in the received signal strength (link budget), we decided to use this model in our simulations, in order to calculate the quality of connections between sink nodes (in our model referred to as the \(q\) value). Among many other factors, the path loss model depends on frequency, antenna height, receive terminal location, relative to obstacles and reflectors and link distance. The _free space path loss_ model is a type of path loss model, which represents realistic empirical propagation loss model, and takes into consideration distance and frequency--for this reason, it is the perfect choice for our estimations. In order to calculate exact \(q\) values utilized in our simulations, we used technical specifications of Mica2 and TelosB sensor devices in order to obtain their physical characteristics (RF power, frequency, receive sensitivity). The exact \(q\) value calculation formula is given by the following equation:  
\[q=(t_{p}-20\times\log_{10}(d)+20\times\log_{10}(f)+32.44)\times(-1) \tag{1}\]  
where:  
\(\bullet\)\(t_{p}\) is the RF power of transmitter, given in dBm  
\(\bullet\)\(d\) stands for the distance between two adjacent sink nodes, expressed in km  
\(\bullet\)\(f\) represents the frequency of the device, in MHz  
\(\bullet\)\(32.44\) is the constant value (if \(d\) and \(f\) are given in kilometers and megahertz, respectively)  
The \(q\) value defines the quality of the connection and is calculated using the above formula. It is represented as non-negative real number (\(q=\{q\in\mathbb{R}\,|\,q\geq 0\}\)), where the lower the \(q\) value, the better the connection quality. The success of WSN-based monitoring applications requires the delivery of high-priority events to relay nodes without any loss from the original sources to the final destination.