## 5 TraSLowPeR: Experimental Performance Comparison against Other Traffic Surveillance Protocols  
A central and strongly original aspect of our TraSLowPeR-related research is the willingness to analyze and evaluate the performance of all considered protocols under realistic conditions, by using real traffic flow data obtained from the actual sampling of real intersections inside a road network based on real intersections in the city of Bologna. Two different scenarios where investigated, named Pasubio and Andrea Costa (from the actual names of the primary roads included), which represent two cross intersections of multiple lane roads regulated by traffic lights, particularly interesting in the city of Bologna because characterized by high traffic during the rush hours, with frequent slowdowns and tailbacks. Since both the iETRIS framework and the examined traffic surveillance protocols rely on pseudorandom number generators, we executed 20 different simulation runs with the same configuration parameters, altering each time the configuration of the employed random number generator (used at the iTetris level to generate the random instants for sending reply messages from the node to the RSU and at the ns-3 level to evaluate if messages collided), and we averaged them to obtain the final results. About protocol configurations, we have selected the parameter values shown as optimal in the original papers (see Table 1) for all simulations. In fact, digging into the papers presenting the three protocols we compared to, they neither detail the processes to optimally tune these parameters nor they report about any guarantee on the convergence of such tuning process to an optimal value. Consequently, also for this comparison motivation, we decided to consider the impact of the values of these parameters on performance outside the scope of this paper. \begin{table}
\begin{tabular}{c c} \hline
**Protocol** & **Configuration** \\ \hline \multirow{2}{*}{Mobsampling} & Mean poll time T: 5 s \\  & Transmission jitter: 200 ms \\ \hline \multirow{2}{*}{Capture recapture} & Message frequency: 10 Hz \\  & Message frequency: 10 Hz \\ \multirow{2}{*}{Jackknife estimator} & Collection rounds t: 10 \\ \hline \multirow{2}{*}{TraSLowPeR} & Reply windows: 100\(\div\)300 ms \\  & Total round robin time: ACosta 1.2 s; Pasubio 1.3 s \\ \end{tabular}
\end{table} 
Table 1: Configuration parameters of the 4 compared protocols. In particular, the configuration settings used for the iETRIS simulator were 50 ms as time step, ns-3 version 20 configured to use the IEEE 802.11p protocol at 5.9 GHz with 6 Mbps bandwidth, with a transmission power for the RSU and the vehicles of 20 dBm, which gives a transmission range of approximatively 170 m. The Jackknife estimator protocol has different outputs depending on the type of estimator used; for the sake of briefness, we present here only the results obtained with the \(N1\) estimator, which demonstrated to be the best one in the considered scenarios in our preliminary experiments; anyway little performance difference was observed for different estimators in all the tested scenarios. To evaluate the performance of all the four traffic surveillance solutions, we used 30 min of real traffic traces collected during the morning rush hours period that provides a maximum vehicle density of about 100\(\div\)120 nodes inside the communication range of the RSU. To improve the readability of the reported charts, also by removing border effects that are not significant for the regular and continuous working of the protocols over real application scenarios, we present only the values collected between 500 s and 1500 s. Different penetration rates are simulated by randomly assigning wireless connectivity capabilities only to the selected percentage of vehicles (all connected vehicles collaboratively participate to the protocols), so that all the nodes (either connectivity-equipped or not) are still inside the simulation and \"moved\" by the mobility sub-simulator SUMO.