# An Energy Efficient Routing Approach for Cloud-Assisted Green Industrial IoT Networks
## 6 Experimental Results and Evaluation
### Simulation Results and Discussion
Consequently, it prolongs the network lifetime as compared to others. On the other hand, as compared to OF-EC, OF-ER provides a better network lifetime because it also considers the resources during the parent selection process, however, it does not include the radio duty cycle, which is one of the key aspects of evaluating the energy consumption of a node. Moreover, the result shows that a multi-queuing based traffic differentiation scheme in RAROF can prolong the network lifetime. This is because data packets are prioritized to access the channel, through which the tendency of packet drop reduces significantly, consequently decreases packet retransmission and saves the node's energy. To obtain high reliability when routing critical data packets, higher priority is given to these packets in channel contention than the regular packets. For this, a node uses its reserved slots for critical data packets and contention access period for regular data packets. Due to the prioritization,  
Figure 3: Impact of transmission range; (**a**) energy cost per data received, (**b**) number of nodes alive in the network, (**c**) packet delivery ratio (PDR) in percentage, and (**d**) network lifetime in seconds. RAROF not only achieves the higher PDR but also increases the network lifetime by reducing the packet retransmission. Afterward, we examined the impact of the varying traffic load on RAROF performance. To this end, we set the transmission range of each node to 60 m. To study the network performance in terms of energy efficiency, reliability, and lifetime, the varied traffic load is offered from 15 to 60 packets per minute. In Figure 4a-d, we have presented the performance of OFs considering different traffic loads. Figure 4a illustrates that the network with higher traffic load has increased energy consumption while delivering data successfully to the destination. The great deal of energy expenses is conserved by RAROF during data delivery under high traffic load. Whereas, OF-EC and OF-ER have comparatively consumed higher energy for successfully delivering data packets. In Figure 4b, it can be seen that as the traffic load increases, the number of alive nodes decreases significantly for all OFs. However, as compared to others, RAROF obtains a higher number of alive nodes in the network. After these analyses, we examined the reliability of the network under different traffic load. Figure 4c shows that as the traffic load increases, the packet delivery ratio of RAROF, OF-ER, and OF-EC decreases. This tendency can be described by the fact that under heavy traffic flow, generated and received data packets often backlogged at the node's buffer, which leads to more retransmission and packet loss, resulting in a lower PDR. However, in this regard, RAROF prioritizes the traffic types and differentiate them using a multi-queuing system, as a result, achieves higher PDR as compared to others. Moreover, RAROF not only differentiates the traffic type but also aware of the node's buffer utilization during route construction. Therefore, it achieves a minimum and maximum reliability of 44% and 86%, respectively, when the traffic load is 60 and 15 ppm. On the other hand, OF-ER maintains higher reliability than OF-EC, one of the main reasons for this achievement is that it includes the node's queue utilization metric during route construction. From Figure 4d, we can observe that the network lifetime decreases constantly for all OFs with the increased traffic load. The network  
Figure 4: Impact of traffic load; (**a**) energy cost per data received, (**b**) number of nodes alive in the network, (**c**) PDR in percentage, and (**d**) network lifetime in seconds. topology constructed under RAROF alleviates partition for a long time as compared to OF-ER and OF-EC. This indicates that RAROF can delay the death of a node in the network due to the node's energy consumption. After these assessments, we analyzed the effect of the reporting interval on network partition.