# Collision Avoidance Geographic P2P-RPL in Multi-Hop Indoor Wireless Networks
## 4 Performance Evaluation  
In this section, we evaluate the performance of P2P-RPL, ER-RPL, Location-Aided P2P-RPL, and Collision Avoidance Geographic P2P-RPL using the Cooja network simulator for Contiki Operating System (OS) [41]. The proposed algorithms, Location-Aided P2P-RPL and Collision Avoidance Geographic P2P-RPL, use a location-constrained forwarding zone for a P2P-RPL-based route discovery procedure. Collision Avoidance Geographic P2P-RPL additionally uses the elastic trickle timer algorithm during the route discovery procedure with the location-constrained forwarding zone. The algorithms are implemented based on modules of ContikiRPL library and P2P-RPL implementation [37; 38]. Preliminary testbed experiments with the EVB1000 platform were performed for the IR-UWB-based Cooja network simulation parameter settings. We used the default Contiki UDP on top of the nullrdc layer and the Decawave low-level radio driver with radio adaptation codes [42]. The main elements integrated on the EVB1000 were the following: a STM32F105 ARM Cortex M3 microcontroller (with 64 kb RAM memory and 256 kb Flash memory), a DW1000 transceiver (based on standard 802.15.4-2011), and an omnidirectional antenna. The UWB radio configurations are stated in Table 1.  
The end-to-end delay measurements were evaluated using Contiki's RTIMER with a resolution of 30.5 us. We changed the hop length between the sender and the destination node from 1 to 4 to assess the performance with various path lengths. The inter-message interval (IMI) was set to 1 s. The average one-hop delay is presented in Table 1.  
Based on the testbed experiment results, simulation studies were conducted to study the localization and routing performances in multi-hop LLNs. In network configurations, the static nodes and the mobile nodes were deployed in a \(75\times 75\) m\({}^{2}\) network area. The number of static nodes varied from 25, 36, to 49 and the number of mobile nodes was set to 5. The static nodes were placed in grid deployment with some randomness: the static node's position was \((10a\pm\Delta x,10b\pm\Delta y)\), where \(-10\leq\Delta x\leq 10\), \(-10\leq\Delta y\leq 10\). Assuming that node ID is \(U\), the value of \(a\) and \(b\) were obtained through \(U=\sqrt{N}\times a+b\), where \(N\) is the number of static nodes. Five mobile nodes were moving continuously with slow random walking speed and operated as leaf nodes without intermediate route forwarding features in the route discovery procedures [43; 44]. The four outermost static nodes were anchor nodes with prior known positions. In this simulation study, we defined the concept of the average node degree for the performance evaluation in terms of the node density. The average node degree was defined as the average number of one-hop neighbors of a node in the network. The higher the average node degree was, the higher the node density was. The average node degree varies from 6, 9, to 12. Figure 7 and Table 2 show the CDF of the average estimated errors for the proposed localization algorithm in terms of the average node degree in two cases: with and without mobile nodes. As shown in Table 2, localization errors remained low regardless of the average node degree when mobile nodes existed. The average location errors were 130.89, \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Channel number & 5 \\ Channel center frequency & 6489.6 MHz \\ Channel bandwidth & 499.2 MHz \\ Nominal bitrate & 6.81 Mbps \\ Mean PRF & 15.6 MHz \\ Preamble length & 128 symbols \\ Transmitter electronics (\(E_{TX-elc}\)) & 33.97 nJ/bit \\ Transmitter amplifier (\(\epsilon_{amp}\)) & 6 pJ/bit/m\({}^{2}\) \\ Receiver electronics (\(E_{RX-elc}\)) & 14.56 nJ/bit \\ Average one-hop delay & 259.25 us \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The UWB radio configuration parameters. 123.73, and 121.99 cm when the average node degrees were 6, 9, and 12, respectively.