## 5 Performance Evaluation and Results Analysis
### Control Message Overhead per Delivered Data Message  
The control message overhead per delivered data message (CMO) metric shows the number of control message transmissions required to deliver each data message successfully. As in the previously presented metric, the results of the CMO are directly related to the packet delivery efficiency. Although control messages are not used during the forwarding of data packets, it is possible to count the overhead generated by the nodes to construct the path used to deliver the data messages. Thus,  
Figure 7: Average energy spent per delivered data bit in function of number of nodes.  
calculating the ratio between the quantity of control message transmission used to discover the routes and the number of data packets delivered, it is possible to obtain the mean of control message transmissions required to deliver each data message. Thus, this metric is calculated according to Equation (4):  
\[CMO=\frac{\sum_{i=1}^{N}CMt_{i}}{\sum_{i=1}^{N}Pr_{i}} \tag{4}\]  
where \(N\) is the number of nodes in the network, \(CMt_{i}\) is the total number of control message transmissions performed by each node \(i\), and \(Pr_{i}\) is the number of data packets received by each node \(i\).  
The results obtained for the CMO metric are presented in Figure 8. In all studied scenarios, the proposed solution was able to obtain better results concerning the compared approaches. The main advantage of using LOADng-IoT is the reduction in the number of control message transmissions during the route discovery process. The mechanism of Internet route discovery, which was inspired by LOADng-SmartRREQ, has reduced the number of control message broadcasts avoiding the nodes outside the already known route received and processed control messages irrelevant to them. In addition, the facility provided by the IRC has allowed the nodes to improve the IN discovery, since the route discovery is directed to a previously known IN using unicast transmissions. Notice that the mobility of the INs was not able to affect the benefits of IRC. The capacity of LOADng-IoT converting a unicasted RREQ into a normal RREQ allows the node to discover a path to an Internet-connected node even if IRC has directed the RREQ to an IN no more available. In the results from all studied scenarios, LOADng-IoT outperforms LOADng and LOADng-SmartRREQ being able to, in some cases, reduce by three times the number of control message transmissions required to deliver one data message. It is also important to note that, in the random and mobility scenarios, the control overhead is about two times greater than in the grid sparse scenario. In addition, in general, the number of control message transmissions is elevated in relation to the number of delivered messages. This behavior is justified by the configurations adopted in the network and protocol parameters. The data throughput is low and the valid times of the routes are short, meaning that a high number of route creation processes is required by the nodes. These parameters were purposely adjusted in this way to permit a better analysis of the behavior of the studied protocols.  
Figure 8: _Cont._