# Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities
## 4 Simulations
### Results
Unlike most of the other solutions that do not cope with the optimal transmission system, our proposed architecture adopts a constraint-oriented decision for the selection of forwarders among IoT nodes to gateway nodes. The mobile sink also makes it more realistic to gather the incoming observed data and transmit them to the users' end with the integration of the 5G network. It has a direct association with gateways to increase the network throughput with nominal network overhead. Moreover, the utilization of a 5G network increases the bandwidth capacity of the shared channels and maximizes the ratio of data delivery. Figure 6: Scenarios of (**a**) analysis of the success ratio under a varying data rate of 30 to 150 bits/s, and (**b**) analysis of the success ratio under a varying number of rounds, from 1000 to 5000. Figure 7 illustrates the performance of the proposed architecture against existing solutions for complexity time under varying data rates and several rounds. It was seen that it significantly reduced the rate of response time by an average of 13% and 15%, unlike the existing solutions. In the high data generation factor, it was noticed that existing solutions incurred rapid route re-organization and disruption due to the constraint resources of IoT technology being overlooked. In addition, malicious nodes could drop the public health data and include false control packets that further increased the load and created congestion in the transmission medium. Therefore, medical data experienced a delay in forwarding to the end-users and as a result, users were not able to obtain a response to their demands on time. On the other hand, the proposed architecture associates the network nodes with a secure cryptosystem and makes the information private against threats. In addition, it offers authentic communication in the existence of bogus packets and eliminates the irrelevant activities without confirmation of the nodes' uniqueness. Accordingly, it decreases the probability of route damages, and ultimately, it reduces the value of the network complexity. Figure 7: Scenarios of (**a**) analysis of complexity time under a varying data rate of 30 to 150 bits/s, and (**b**) analysis of response time under a varying number of rounds, from 1000 to 5000. Figure 8 illustrates the performance of the proposed architecture in the comparison of resource consumption under varying data rates and number of rounds. Based on the results, it was observed that it decreased the consumption by an average of 14% and 17%, unlike the existing solutions. This was due to most of the computing operations being done in high resource-oriented gateways and sink nodes. All the secured keys are generated on these high-power nodes, which only the connected nodes use to ensure data security against attacks. Moreover, lightweight XoR operations in data encryption and decryption impose the least storage and processing overheads on the connected end-users IoT devices. Furthermore, the integration of storage centers provides a robust solution for storing big data and decreases the communication overhead. Figure 8: Scenarios of (**a**) analysis of resource consumption under a varying data rate of 30 to 150 bits/s, and (**b**) analysis of resource consumption under a varying number of rounds, from 1000 to 5000.