# CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications
## 5 Performance Evaluation
### Impacts of Bursty Traffic Arrivals  
In this part, we illustrate the importance of responsiveness under a highly dynamic traffic model. Here, we consider the impact of dynamic traffic bursts at different time instants in an industrial monitoring network. Figure 11 shows a network topology and two source nodes suffering from an unusual event occurring in the monitoring region. The occurrence of the two events and their burst periods is given in Table 3. We assume that the event occurs near sensing node 9 and 16 during the time interval as described. Only sensing node 9 and 16 can detect the occurrence of events. Moreover, the event reporting frequency of the sensing node is greater than the continuous monitoring reporting frequency. Furthermore, every event injects data traffic with a rate of 16 packets every second, and there are two bursts for each event.  
Figure 11: Sudden event occuring network topology.  
Figure 10: Data reliability over different number of nodes: (**a**) Packet loss ratio; (**b**) Packet receiving ratio; and (**c**) Throughput in bytes.  
In Figure 12a, we observe that the adaptation capability of CoAR is higher than that of other approaches. Along with ensuring steady flow under low traffic loads, the CoAR is able to retain higher reliability (the packet receiving rate at root node) than ECRM and RPL even at bursty traffic durations. CoAR can effectively tolerate the burst because of its efficient congestion detection scheme and queue monitoring policy. As shown in the figure, we can note that the improved reliability of the CoAR is highlighted in terms of receiving packet rate at the time of two bursts (100-150 s, 200-250 s interval). This superior performance can be attributed to mainly, CoA-OF and adaptive congestion detection scheme. When the event occurs, the sensing node injects heavy traffic in the network and the queue occupancy of the parent increase sharply. As RPL does not have an efficient scheme to handle a large number of burst packets well, the packets are backlogged at the parent node in a very short interval. Therefore, RPL enters in an overloaded condition, which results in queue loss and delay hence the performance degrades. The ECRM is prone to congestion situation due to static congestion detection scheme and consecutive buffer overflow-based parent change policy, resulting in degraded network performance. Thus, dynamic traffic arrival, which is often a common phenomenon in industrial monitoring IoT application, can be better addressed and accommodated by our proposed scheme.  
Figure 12b shows the average end-to-end delay. When the burst traffic arrives in the buffer, the overflow of packets is more likely to happen, leading to retransmission and queue lost. As shown in the figure, during the burst period, the amount of delay using CoAR is the least compared to other protocols. CoAR uses the congestion degree to determining the congestion situation adaptively which indicates the trend of queue fluctuations and thus smooths the burst traffic arrivals as much as possible. As a result, it achieves the better reliability and decreases packet loss. This, in turn, leads to a decrease in end-to-end delay.