# An Energy Efficient Routing Approach for Cloud-Assisted Green Industrial IoT Networks
## 6 Experimental Results and Evaluation
### Simulation Results and Discussion  
The performance of OF-EC, OF-ER, and RAROF are intensively evaluated in various aspects. We first examine the impact of transmission range for all OFs in terms of energy efficiency, lifetime, and reliability. Figure 2(a) shows the energy expenditure of a successfully delivered data packet at the destination by OF-EC, OF-ER, and RAROF with respect to the varied transmission range. As the transmission range increases, the energy consumption of each OF decreases accordingly. It is clear that the reduced energy consumption can be achieved with RAROF compared to other OFs. This is because, the higher transmission range helps each node making more successful data transmission, which reduces the number of lossy links that a node should traverse to reach its destination. Besides, the traffic differentiation through the multi-queuing technique allows the node to prioritize the data packet according to the traffic types. Furthermore, the RAROF adopts the duty cycle information in a routing process, which enables nodes aware of the active and inactive status. In this manner, the possibility of re-transmission is reduced, which results in an energy cost reduction. As compared to OF-EC, OF-ER have achieved better energy cost because it considers various metric while selecting parent such as queue, delay, link quality, etc. From Figure 2(b), we notice that for the varied transmission capacity, RAROF achieves the higher numbers of alive nodes in the network compared to OF-ER and OF-EC. When the transmission range of each node is 60 m, RAROF outperforms OF-ER and OF-EC by achieving about 11% and 21% of more alive nodes, respectively. On the other hand, when the transmission range is 20 m, the performance is very similar. Therefore, we consider 60m as default for our simulation experiments. Figure 2(c) shows the packet delivery ratio of OF-EC, OF-ER, and RAROF in percentage under varying transmission range. The result depicts that with the increasing transmission range, the packet delivery ratio also increases for all OFs. Nevertheless, RAROF obtains the higher PDR than OF-EC and OF-ER. Compared to others, RAROF significantly achieves more alive nodes in the network, which provides an opportunity to find the optimal routing path, resulting in the higher PDR. Besides, it adopts a multi-queuing approach for traffic differentiation, and data packets are forwarded, to the proper channel (i.e., fixed sized slots or reserved slots), according to the traffic priority. Thus, RAROF can maintain its reliability of a maximum of 86.7% and a minimum of 32.5% when the transmission range is 60 and 20 m, respectively. In contrast, OF-ER improves its reliability by 15.4% and 4.5% higher than OF-EC when the transmission range is 60 and 20 m, respectively. It wasexpected because OF-EC is not aware of its resources in terms of queue utilization and the number of overburden nodes. On the other hand, at the transmission range of 60 m, OF-EC maintains the reliability of a maximum of 56.7%, which is about 30% less than RAROF, and it is not acceptable for emergency monitoring application of IIoT. Besides, during parent selection, both OF-ER and OF-EC do not allow to be aware of nodes' sleep and awake states, which leads to higher packet retransmission, eventually affecting the network reliability. As can be seen in Figure 3d, with the increasing transmission range, the network lifetime also increases consistently. The result reveals that RAROF can effectively delay the occurrence of the network partition as compared to OF-ER and OF-EC. When the transmission range is 20 and 60 m, RAROF shows the superiority in the network lifetime performance than OF-ER and OF-EC by about 5.2% and 8.7% and 8.2% and 16.3%, respectively. This is because the routing mechanism of RAROF can effectively reduce the interruption of communication due to network partition. Besides, RAROF makes use of network resources effectively during the route construction process, resulting in more numbers of alive nodes.