# An Energy Efficient Routing Approach for Cloud-Assisted Green Industrial IoT Networks
## 6 Experimental Results and Evaluation
### Simulation Results and Discussion
In this regard, we utilized various reporting intervals ranging from 2 to 8 s. It is define as the time interval between the arrival of data packets. We set the transmission range of each node to 60 m. Figure 4(a) shows that RAROF can keep the nodes alive to a higher number as compared to other OFs. It also illustrates that as the reporting interval increases, so does the number of active nodes in the network. When the interval is 2 s, the number of alive nodes of OF-EC, OF-ER, and RAROF are almost the same, because the low inter-packet interval leads to higher energy consumption. However, in this situation, RAROF obtains 4.2% and 5.9% more alive nodes than OF-ER and OF-EC, respectively. Then, we examined the node's lifespan over time. The number of nodes alive in the network is shown in Figure 4(b). From the result, we can observe that the alive nodes in the network decrease for all OFs over time. Nevertheless, RAROF comparatively achieves more alive nodes during simulation time. OF-EC, on the other hand, achieves the lowest number of active nodes over time. Similarly, we examine the network lifetime in terms of the varied reporting interval. Figure 5(a) illustrates the lifetime of the network with respect to the reporting interval. The result depicts that with the increasing time interval, the lifetime of the network also increases significantly. This is because the higher the intervals between packets, the lesser the node's buffer filled, resulting in lower packet loss due to buffer overflow, which eventually reduces packet re-transmission and thereby saves energy. At each reporting interval, the network lifetime in RAROF increases, which shows that RAROF can effectively reduce the death of nodes due to energy-constrained. After that, we analyzed the network lifetime over time. Figure 5(b) shows that for each OFs, the network lifetime decreases over time. From the result, it is clear that the network lifetime of RAROF is higher than OF-EC and OF-ER. Moreover, it can be noticed that the occurrence of a network partition is gradually rising with time, and for all OFs, the energy-constrained is negligible at the initial stage of network operation is low. However, OF-EC is most energy vulnerable as compared to OF-ER and RAROF. Next, we examined the overhead comparison of the OFs. For this, we only considered the overhead of the DIO control messages of each node. In this simulation experiment, we set the traffic load to 15 ppm, and the transmission range of each node set to 60m. We look into more detail about the overhead of route construction and topology management through Figure 6(a)-d. Therefore, we take into account the traffic load and transmission range to analyze the overhead. Figure 6(a) shows the average parent change per node vs traffic load. In a resource-constrained network, frequent parent change also has an impact on energy consumption. Consequently, the network lifetime may be affected. However, the average parent changes in RAROF is lower than others. It indicates that RAROF selects a reliable next-hop node than OF-ER and OF-EC. This is because RAROF selects the parent based  
Figure 5: Nodes alive in the network; (a) number of nodes alive in terms of reporting interval, (b) number of nodes alive over time. on the minimum function of the NVI metric. Besides, RAROF can be aware of the node's resources availability during parent selection. Likewise, Figure 7b shows that RAROF generates a minimum number of control packet even when the traffic load becomes heavy. When the traffic load is high, OF-EC incurs comparatively more routing overhead than RAROF and OF-ER. Furthermore, we have investigated the different aspect of topology management with varied transmission range. To this end, we consider the DODAG repair execution and DODAG depth as an evaluation criterion. The DODAG repair execution is the topology repair frequency performed by the DODAG root, and DODAG depth is the number of hops from DODAG root. From Figure 7c, it can be seen that OF-EC frequently triggers DODAG repair compared to OF-ER and RAROF.