## 2 Related Work
### State of the Art of Software Metrics in the Estimation of Link Quality in Wireless Sensor Networks  
Because the variation in the PER defines the sensitivity of the wireless sensor node, it plays an important role in the robustness of communication, energy efficiency, and routing protocols.  
The PER is the transmission error, where the data transmission unit receives erroneous information from one of its sources. This might happen due to interference, attenuation, or hardware failure. It can also result from unreliable data sources. Packet errors are measured in percentage as the number of packets lost divided by the total number of sent packets. However, the packet reception ratio (PRR) calculates the reception ratio in which the received packet is correct.  
\[PRR=1-PER=\frac{n_{received}}{n_{sent}} \tag{1}\]  
where \(n_{received}\) is the total number of successfully received packets by the receiver, and \(n_{sent}\) is the total number of the sent packets by the transmitter.  
The industrial environment is a challenging field for sensor node deployment because the link quality is constantly affected by electromagnetic waves, noise, and interference from different technologies. The estimation of link quality is a needed process to define network reliability, such as in [20], where a PRR was used in addition to the average of the signal to noise ratio (SNR) and link quality indicator (LQI).  
The PER metric is an essential software-based metric in wireless networks, especially in sensor nodes and mobile ad hoc networks, because the reliability of packet reception ratio has a fundamental impact on the efficiency of wireless communication [19].  
Recently, PER has drawn much attention due to its advantages: simplicity and efficiency. In [21], a theoretical bit error rate (BER) model of IEEE802.15.4 and a PRR estimation approach were proposed using a simulation platform (Matlab 2013a).  
Researchers [22] studied the relationship between system reliability and transmission range using different metrics such as the PRR and symbol error rate.  
In [9], the performance of WuRx was discussed based on two LF amplifier approaches according to the sensitivity, power consumption, and PER. An indoor experiment was carried out inside a building in different rooms and on different floors.  
An author [23] presented sender-side software-based link-quality estimator metrics, the link quality level (LQL) and the expected transmission count (ETX), for approximating  
Figure 5: Organization of different link quality estimators according to [19].  
link quality by counting the ratio of the number of transmitted and retransmitted packets to the number of successfully received packets to build a more reliable routing based on the link quality.  
In [24], the researchers combined both hardware- and software-based metrics and used the PRR to overcome the lost packet information problem and improve the accuracy rate for evaluating a link quality in a WSN.  
In [25], a combination of PER, SNR, and LQI using IEEE 802.15.4-compliant transceivers (2.4 GHz Chipcon CC2420 radio) was used to provide a real-time estimation of the link quality between nodes.  
The results of the previous studies have shown that the PER is strongly correlated with the received signal power, path loss, SNR, etc. Software-based metrics can more precisely estimate link quality than hardware-based metrics. However, using only software-based metrics to evaluate a link quality cannot capture link quality changes in real-time [25].