# Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities
## 4 Simulations
### Results  
This section presents the evaluation results and discussion of the proposed architecture against the existing solution in terms of network packet drop ratio, route breaches, success rate, complexity time, and resource consumption. The experiments were conducted based on the varying data rates and the number of rounds. Figure 4 depicts the performance analysis of the proposed architecture with the existing work in terms of the packet drop ratio and varying data rates and the number of rounds. It was observed that the proposed architecture significantly decreased the packet drop ratio by an average of 12% and 16%, unlike other solutions. This was due to the proposed architecture noticing the bandwidth and transmission load on the selected IoT node for forwarding medical data. It also made use of the gateway nodes that explicitly improved the management of the network nodes and their association in clusters using the \(k\)-medoid algorithm, which increased the stability of the network with an increased delivery confidence level. Moreover, the proposed architecture exploited a robust secured multi-level algorithm that eliminated the malicious operations on medical data and increased the successful packet delivery performance. Figure 5 depicts the performance evaluation of the proposed architecture with other solutions in terms of route breaches under varying data rates and the number of rounds. It was seen that the proposed architecture decreased the ratio of route holes by an average of 13% and 15%, unlike the existing solution. It was observed that the existing solution incurred extra communication overheads in routing that explicitly increased the usage of network resources. In addition, the ratio of route breaches rose when the data sending rate increased. It was also observed that with the increasing number of faulty nodes, the number of bogus packets was too high and affected the data integrity. As a result, most of the time, it compromised sensitive information with several times of re-transmission. Therefore, the design of the proposed architecture focuses on providing a more secure and authentic solution for decreasing network threats for connected users. It provides \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Medical nodes & 50 \\ Wireless links & Asymmetric \\ Data packet & 64 bit \\ Transmission power & 3 m \\ Initial energy & 2 J \\ Cache memory & 15 Mb \\ Size of payload & 512 bytes \\ Rounds & 1000 to 5000 \\ Gateway nodes & 10 \\ Malicious nodes & 10-20 \\ Observing field & \(10\times 10\) m\({}^{2}\) \\ Frequency & 2.4 GHz \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Default simulation factors. a multi-level of security, i.e., from IoT nodes to gateway nodes, from gateways nodes to mobile sink, and from the mobile sink to storage centers. The proposed architecture assists with reliably connecting users and offers secured delivery performance against malicious attacks. Figure 4: Scenarios of (**a**) analysis of the packet drop ratio under a varying data rate of 30 to 150 bits/s, and (**b**) analysis of the packet drop ratio under a varying number of rounds, from 1000 to 5000. Figure 6 illustrates the experimental results of the proposed architecture in terms of the success rate against existing work and varying data rates and the number of rounds. Based on the numerical finding, it was noticed that the proposed architecture increased the delivery ratio by an average of 11% and 14%. This was because, based on the lowest cost, the network nodes were divided into clusters and they associated with their nearest gateway  
Figure 5: Scenarios of (**a**) analysis of route breaches under a varying data rate of 30 to 150 bits/s, and (**b**) analysis of route breaches under a varying number of rounds, from 1000 to 5000.  
nodes. The deployed gateway nodes reduced the energy consumption of IoT nodes in forwarding the collected data.