# mIoT Slice for 5G Systems: Design and Performance Evaluation
## 5 Performance Evaluations
### Simulation Results and Discussion
To summarize the results in Figures 5 and 6, a proper tuning of the inactivity timer T affects the ratio between the signaling related to ACN bearer establishment/re-setup and updates, with gains compared to 4G up to three orders of magnitude when increasing T considering the scenario in Table 1. A proper tuning of the maximum number of PhDs for a VD (U) positively impacts the UP resource utilization, with a gain with respect to 4G of three orders of magnitude when increasing U considering the scenario in Table 1.  
After analyzing the behavior of 4G and 5 GS mIoT in a specific scenario where all devices have the same AP, we now consider a realistic scenario with different classes of devices, each with different UE density and AP. We consider the traffic model in [26; 27], which are summarized in Table 2. For 5 GS mIoT, we assume that a VD gathers PhDs belonging to the same device class to reflect the fact that different traffic types may require different QoS treatment due to the nature of their traffic or due to the SLAs between the owners of the devices and the operator. For 5 GS mIoT, all classes of devices have U = 100 and T = 1 min. The analysis shows that 5 GS mIoT slice is able to guarantee a CP signaling reduction of \(\sim\)60% with respect to EPS (Figure 7) when considering a practical scenario with different types of active devices with an increase in the UP resource utilization up to 2 orders of magnitude (Figure 8). In addition, it is worth underlining the benefits introduced by the 5 GS mIoT in reducing the impact with respect to 4G of applications with massive CP signaling (i.e., gas meters and pay-as-you-drive in the considered scenario) in both CP and UP. A further analysis can be found in Table 3, which lists the number of enabled bearers assuming a deployment of \(10^{4}\) RAN nodes. The 5 GS mIoT slice has on average a reduction of about two orders of magnitude in the number of enabled bearers compared to 4G, which further testifies the reduction of CP load in the CN introduced by the 5 GS mIoT slice. Given the fact the network entities in the CN can support only a limited number of bearers simultaneously active, 5 GS mIoT is an effective solution to increase the number of supported UEs without requiring more capable (and thus expensive) network entities. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Device Class** & **Device Density** & **Activation Period (AP)** \\ \hline Water meters & \(10^{4}\) UE/km\({}^{2}\) & 12 h \\ Electricity meters & \(10^{4}\) UE/km\({}^{2}\) & 24 h \\ Gas meters & \(10^{4}\) UE/km\({}^{2}\) & 30 min \\ Bike fleet management & 200 UE/km\({}^{2}\) & 30 min \\ Pay-as-you-drive & 2250 UE/km\({}^{2}\) & 10 min \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Traffic parameters of device class considered in the analysis in Figures 7 and 8, and Table 3.  
Figure 7: (**a**) CP signaling composition among different classes of devices in 4G; and (**b**) CP signaling composition in 5 GS mIoT and reduction with respect to 4G. For 5 GS mIoT, all classes of devices have U = 100 and T = 1 min. Finally, the analysis in Figure 9 aims at understanding the CP signaling generated with 4G systems and the related benefits introduced by the 5 GS mIoT in scenarios with massive load on the RAN, as envisaged for 5G mIoT use cases with up to millions of IoT devices per cell. To this end, an analysis has been conducted varying the device density up to 10 \(\times\) 10\({}^{6}\) UE/km\({}^{2}\). To better isolate the behavior of the RAN, only one RAN node is considered. All UEs are assumed to belong to the same class, where AP = 2 min and AP = 10 min were considered. The bearer expiration timer is T = 1 min. Finally, for 5 GS mIoT, the maximum number of PhDs per VD is U = 100. From this analysis, we can note that the CP signaling reaches a maximum value before starting the congestion, i.e., high collision in the RA procedure.