## 4 Investigating Parameters' Impact on Beacon Rate Adaptation
### Parameters Used and Their Significance  
In this subsection, we discuss the parameters used in our proposed protocol and their significance. In VANETs, the beaconing rate can be influenced by different parameters. Through surveying the literature and conducting extensive simulations, we found that beaconing rate adaptation was highly affected by five parameters as follows: channel busy time, mobility, packet delivery ratio, number of neighbors, and signal-to-interference-noise ratio. The channel busy time (CBT) is a good measure for channel load [44; 45]. A high CBT means the channel is more occupied; in that case, the beaconing rate should be reduced to alleviate the load on the channel. The CBT is defined as the proportion of time the channel is sensed occupied by vehicle \(x\) (vehicle \(x\) is the vehicle that will adapt its beaconing rate) during a monitoring interval because of vehicle \(x\) or its neighbors' activity. The acquisition of the CBT value occurs when the signal strength received by the measuring node surpasses the clear channel assessment threshold (CCA) over a specified time window. The \(ChannelBusyTimeFactor\) is computed as:  
\[ChannelBusyTimeFactor=\frac{CBT_{x}-CBT_{min}}{CBT_{max}-CBT_{min}} \tag{1}\]  
where \(CBT_{x}\) represents the duration where vehicle \(x\) detected the channel as occupied during the monitoring interval. \(CBT_{min}\) and \(CBT_{max}\) denote the minimum and maximum channel busy times for vehicle \(x\) and its neighbors, respectively. Mobility is one of the most important parameters in VANETs, since it reflects the vehicles' movement and traffic status. In high traffic mobility, the beaconing rate should be increased to ensure that more packets reach the fast and distant vehicles. The proposed schemes in the literature use a mobility factor that takes into account either the distance between vehicles or the speed of vehicles [20; 36; 41; 46; 47; 48; 49]. However, in this work, we use a more representative vehicle mobility factor, which we proposed in our preliminary work [50; 51; 52]. It considers both the distance between vehicles and the speed of vehicles. Hence, we obtain the mobility factor by computing the distance \(d_{i}\) between vehicle \(x\) and its neighboring node \(i\). We use the speed to calculate the distance, \(d_{iT_{b}}\), traveled by vehicle \(i\) during the beacon interval \(T_{b}\):  
\[d_{iT_{b}}=s_{i}*T_{b} \tag{2}\]  
where \(d_{iT_{b}}\) is the distance traveled by vehicle \(i\) during the beacon interval, \(s_{i}\) is the speed of vehicle \(i\), and \(T_{b}\) is the beacon interval. We then calculate the average \(K\) of (\(d_{i}+d_{iT_{b}}\)) over all the neighboring nodes (\(i=1,\ldots,n\)) of vehicle \(x\), as shown in Equation (3). \[K=\frac{\sum\limits_{i=1}^{n}(d_{i}+d_{iT_{b}})}{n} \tag{3}\]  
Determining the final mobility factor value requires dividing \(K\) by the transmission range \(R\) and subtracting a smoothing factor \(\alpha\), as depicted in Equation (4). \[Mobility=\frac{K}{R}-\alpha \tag{4}\]  
The packet delivery ratio (PDR) reflects the link quality [53]. The PDR is influenced by the quantity of transmitting vehicles. With an increase in the number of sending vehicles, the PDR tends to decrease. This is attributed to the diminished success probability in accessing the medium, resulting from an escalation in the number of vehicles contending for channel access [54]. The PDR is characterized as the ratio of packets successfully received to the total number of packets transmitted within the current time interval. In this time frame, any packet received from a neighboring vehicle situated within the transmission range is deemed as a successfully received packet. The number of neighbors (local density) is a very important parameter that needs to be considered in VANETs [18; 21; 36; 55; 56; 57]. The number of neighbors needs to be estimated before attempting to adapt the beaconing rate.