## 6 Results and Evaluation
### Results Discussion  
All results are summarized and listed in Tables 4-6. Table 4 shows IoT-LAB results for random and uniform 140 M3 wireless nodes while adopting two different objective functions (OF0 and ETX). Experiments in IoT-LAB lasted for 2 h with sending rate of 45 s and with 70 runs. The measured control traffic overhead is considered as the total overhead traffic for all the network nodes during the experiment time. ETX Objective Function is outperforming OF0 in the defined measured metrics as it has the lowest control overhead, latency, and power consumption while providing higher packet delivery ratio than OF0 overall RPL performance, while the network is uniformly distributed and outperforms the results of random network topology. Random networks experienced high latency, more retransmission, network congestion, and higher power consumption. Table 5 shows simulated results of Cooja simulator for a large-scale network using a random network topology while applying OF0 and ETX. Simulation lasted for 1300 s with sending rate 30 s for 1000 nodes, using only one sink node with one RPL DODAG instance. The Cooja simulation output indicates many variations of RPL performance as the network size increased. It reflects higher latency when RPL protocol uses ETX to calculate the routes and less power consumption with the higher delivery ratio. If RPL proposed a high-density network application, which requires low latency like medical monitoring applications, it is recommended to apply OF0, which basically depend on the number of hops to calculate the routing routes as it experiences lower latency than ETX. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Routing Metric (Total nods=140)** & **Uniform Topology** & \multicolumn{2}{c}{**Random Topology**} \\ \hline OF0 & OF0 & ETX & OF0 & ETX \\ Control Traffic Overhead (PKTs) & 78000 & 62000 & 90000 & 70000 \\ PDR \% & 70\% & 85\% & 45\% & 55\% \\ Network Latency (S) & 3.5 & 3 & 7 & 5 \\ Average Energy Consumption (mW) & 2.5 & 1.5 & 4.5 & 3.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: RPL routing metrics results in IoT-lab testbed measured over simulation time. Figure 18: Average power consumption in Cooja simulator for OF0 and ETX with random RPL topology. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Routing Metric (Nods No=1000)** & **Cooja Simulated Topology** \\ \hline  & OF0 & ETX \\ Control Traffic Overhead (PKTs) & 70,000 & 43,000 \\ (PDR) \% & 45\% & 66\% \\ Network Latency (S) & 38 & 70 \\ Radio on Time \% & 2.2\% & 1.1\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: RPL routing metrics results within cooja simulator measured over the simulation time. To be fair, we choose from literature some related work [7; 9; 12; 17] that evaluate RPL protocol using operating system Contiki like our study and based WSN environment in terms of routing metrics and targeting many different platforms and scenarios to test RPL applicability in AMI applications. We compare our RPL evaluations using the experimental network and simulated network with these related works and find that we measured RPL performance using two important objective functions (OF0 and ETX) in terms of four routing metrics (overhead, latency, PDR and power consumption). [PERSON] et al. [7], find that RPL overhead traffic is very high and should be decreased. They didn't measure any other metrics and they use only ETX to find the best path. Their evaluation does not reflect anything about RPL behavior in dense networks or the effectiveness of network physical topology. [PERSON] et al. [9] evaluate RPL in uniform topology and their results showed that RPL overhead is very high, while they mentioned that RPL performance is not affected by the physical topology. In [PERSON] et al. [17] this implementation used hop count to find the best path in medium scale network. Their results lack the RPL end-to-end delay calculation and don't provide RPL behavior in random WSN topology. In [PERSON] et al. [12] they provide small network of 27 nodes and they measure only the overhead.