# Pipe Routing with Topology Control for Decentralized and Autonomous UAV Networks +
## 8 Simulation Results and Discussion
### Performance Metrics  
We measure the performance of our UAV network using several routing and coverage metrics.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Simulation Time & 2000 s \\ Map Area & 6 km \(\times\) 6 km \\ Transmission Range & 1 km \\ Number of UAVs & 30, 50 \\ UAV Speed & 20 m/s, 40 m/s \\ Number of Targets & 1, 3 \\ Channel Range & 11 Mbps \\ Packet size & 1.5 kB \\ Data Rate & 1-3.5 Mbps \\ TTL & 3 s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation Parameters.  
Figure 7: The target locations in a 6 \(\times\) 6 km\({}^{2}\) map. Three different target locations are shown for a single target in (**a–c**) and for a group of 3-targets in (**d–f**).  
The routing properties of the network are measured by the following:  
* _Packet Delivery Ratio (PDR)_: the ratio of total data packets received at the BS to total data packets generated at target UAVs. PDR is a normalized throughput and can be used to calculate other metrics such as flow throughput (PDR \(\times\) data rate) and packet loss ratio (\(1-\) PDR).
* _Route Breaks (\(R_{b}\))_: the number of route breaks per data flow during the simulation duration of 2000 s. Since a route break leads to the discovery of new routes, a lower \(R_{b}\) value means more stable routes and a lower control overhead.
* _Route Up Time (\(R_{u}\))_: The percentage of time a target UAV has a valid route to the BS throughout the simulation (2000 s duration). A higher value is desired, as it signifies a more stable route to BS with fewer data flow interruptions. The coverage properties of the network are measured by the following:
* _Coverage (\(C_{v}\))_: the average percentage of cells on the map visited by UAVs at least once within a given time duration; we prefer a higher \(C_{v}\) in a given duration of time.
* _Coverage Fairness (F)_: this represents how equally all the cells on the map are visited during a given time period, as measured by Jain's fairness index Jain (2016), \[F=\frac{(\sum_{i}x_{i})^{2}}{n\sum_{i}x_{i}^{2}}\] (9) where \(x_{i}\) is the number of scans of cell \(i\), and \(n\) is the total number of cells in the map. A higher value of \(F\) is desired.  
Our proposed pipe routing with topology control scheme (Section 5) is called 'TC-Pipe'. The Pipe routing without topology control (Section 4) is called 'Pipe'. The 'ADDV' routing scheme does not use a pipe region and topology control. The TC-Pipe, Pipe, and AODV routing schemes all follow the BS-CAP mobility model. Pipe routing under the ConCov mobility scheme Pipe (2017) is referred to as 'ConCov-Pipe'. Finally, the relay-based routing scheme uses the BS-CAP mobility model and is called 'Relay' (see Section 7). The suffix \"-20\" (e.g., TC-Pipe-20, AODV-20) indicates UAVs at a speed of 20 m/s, while \"-40\" indicates UAVs at 40 m/s.  
We first discuss the routing and coverage performance of these schemes for different single- and three-target settings without node failure in Section 8.3. Next, we discuss the effect of 20% and 30% node failures on performance in Section 8.4. Finally, we summarize the results in Section 8.5.