# Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture
## 5 Results and Discussion  
The proposed architecture simulation results are compared to those of the traditional healthcare architecture. This traditional architecture has only one coverage tool (the Internet). In addition, it processes the healthcare data as being on importance level. Moreover, the cluster idea is missed, and the management functions are neglected. The performance metrics to measure the efficiency of the proposed healthcare architecture are the delay, energy consumption, packet loss, coverage tool usage, throughput, number of serviced users, and percentage of each data type exchanged through the two architectures (IoT-enabled and traditional healthcare). Figure 8 displays the average delay for the two healthcare architectures. The delay performance metric is measured by calculating the average of processing, transmission, buffering, and propagation delays for sent packets until they reached their destinations. The \(x\)-axis represents the time of simulation, and the \(y\)-axis represents the average delay in \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline Number of patients & 50,000 \\ Number of organizations & 20 \\ Number of users & 100,000 \\ Number of active devices & 200,000 \\ Number of passive devices & 300,000 \\ Distance between organizations & Random range (200–1000 km) \\ Number of wearable devices & 30,000 \\ Number of body sensors & 15,000 \\ Number of mobiles with medical applications & 10,000 \\ Number of HAPs & 5 \\ Number of satellites & 1 \\ Distance between users & Random in range (10–1000 km) \\ Distance between patients & Random in range (10–100 km) \\ Computing centers & Cloud and fog \\ Data types & Text, image, and multimedia \\ Transmission channels & Full duplex \\ Types of sensors & Heterogeneous \\ Number of medical devices & 1000 (distributed) \\ Number of monitoring devices & 20,000 \\ Number of importance queues & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Partial of simulation parameters. Figure 7: Device classification in the proposed IoT-enabled healthcare architecture. seconds. The overall average delay for the proposed IoT-enabled healthcare architecture is less than that of the traditional one because the proposed architecture comprises more than one coverage tool. Therefore, each user can easily change its coverage tool, which means that the healthcare data is exchanged through powerful transmission channels (high bandwidth). The hesitations, which appear in the plots of both healthcare architectures, result from the changing of coverage tools in addition to the dynamic changes in joining/leaving things in the architectures over the simulation time. Figure 9 depicts the energy consumption rates for the two healthcare architectures. The energy, which is consumed by sensing, communication, and processing functions, is used to calculate the energy consumption average for the energy-based nodes. The x- and y-axes represent the simulation time and average energy consumption rates, respectively. The value of energy consumption for the proposed IoT-enabled healthcare architecture is less than that of the traditional healthcare architecture. This result is explained by the availability of alternative coverage tools that allow all of the healthcare devices to communicate in the IoT-enabled healthcare architecture. Thus, the transmitted data are distributed among a greater number of devices than the traditional architecture. Therefore, the size of the transmitted data of each device is decreased, leading to lower energy consumption rates. Furthermore, decreasing the size of processed data, which is achieved by the prioritizer component, is an important factor that positively affect the energy consumption rates. The energy consumption rates are relatively increased over the simulation time for both healthcare architectures due to the increase in data processing requests. Figure 8: Percentages of end-to-end delay. Figure 10 presents the packet loss ratio for the two healthcare architectures.