## 4 Evaluation
### Choice of FLARoute's Parameters  
FLARoute requires the parameters \(\Delta Tb_{i}\), \(\Delta Tg_{i}\), \(\gamma\) and \(B_{th}\) to be set, and here we discuss how changes in these values impact network performance. Node burden can be inferred directly from the number of transmissions. However, instead of counting the number of transmissions to infinity, which does not give a comparable burden for nodes newly joining the network, the observation period can be divided into time slots containing periods of peak traffic. This allows nodes to be observed and burden to be computed for short periods, during which maximum encounters are experienced. We observe that in urban environments, a time slot of 6 h is able to contain at least one period of peak traffic that occurs during rush h (i.e., for a typical working day movement: 07:00 to 09:00 due to encounters experienced while going to work; 13:00 to 14:00 due to lunch break encounters; and 18:00 to 20:00 for encounters while returning home)--note that [PERSON] et al. [18] also exploited the significant rise in traffic experienced during rush h.  
Based on results from several trials, we suggest a time slot of 3 h or 6 h. For \(\Delta Tb_{i}\), we select a time slot of 3 h so that ReBurD responds faster to changes in transmission rate, while we select 6 h for \(\Delta Tg_{i}\) in order for MaxBE to gain insight into the maximum burden on nodes during each rush hour. It is important to note that MaxBE's maximum burden estimate is focused on only neighbouring nodes, rather than every node existing in the network. Also, FLARoute does not require a precise estimate of this value to improve fairness, and can be based on the burden on nodes MaxBE obtains from past encounters in each time slot. Since ReBurD and MaxBE are distributed mechanisms, their time slots can be loosely synchronized with the global time on smartphones. For example, \(\Delta Tb_{i}\) can be from 06:30 to 21:30,..., 12:30 to 15:30,..., 18:30 to 21:30,... Note that such approach only requires a one-off synchronization during initialization and can be updated whenever the node gains access to global time.  
\(\gamma\) denotes the percentage of the maximum burden estimate that is considered as \"low burden\", and determines the number of nodes allowed to forward messages in the less-burden path with FLAFord algorithm (cf., Section 3.2.4). In this regard, a larger value of \(\gamma\) considers higher amount of burden as low. This allows more popular nodes to contribute in the less-burden path, thereby increasing throughput and reducing fairness. Based on results from several trials, we suggest a 20% value for \(\gamma\), as it showed the most optimal throughput-fairness trade-off. \(B_{th}\) is a threshold that denotes when the burden on a node actually matters and starts to reflect noticeably on energy consumption. As we suggested earlier, a desired value of \(B_{th}\) can be obtained from user surveys, in order to meet their satisfaction needs in real-world implementation. Values above or below the desired threshold may either result in more energy consumption on less burden nodes or less delivery guarantees due to more number of nodes dropping messages that are following the less-burden path (cf., Section 3.2.4), respectively. In summary, the parameters \(\gamma\) and \(B_{th}\) determine the trade-off between user satisfaction and throughput.