# A Next-Generation Core Network Architecture for Mobile Networks
## 11 Measurements
The median for the \((10,15]\) call interval level is 2% and the third quartile is 6%. It is encouraging to see that long call intervals (i.e., more-than-30-min bin) are  
Figure 23: The ratio of calls with intervals at different levels. Figure 22: ECDF of the # of calls and call duration over 10 days. (**a**) # of calls; (**b**) Call duration in minutes. the largest percentage of all call intervals. In particular, the median is 67%, meaning that half of the users have 67% of the call intervals longer than 30 min, with the first and third quartiles being 54% and 80%, respectively. In other words, this means that, if a VCN is idle for more than 10 min, we can destroy it and, with high probability, there will be no need to deploy it again for another 20 min or so. To conclude, it is reasonable to measure and use the user call interval patterns in order to determine the life cycle of an entity, i.e., its restart rate. **Summary:** By combining both recommendations, we show how the maximum number of concurrent entities that the network must support is affected by both the number of concurrent calls and the amount of time the UE has to spend into _idle_ mode before its entity gets destroyed. By considering both conditions, we compare three cases: (i) the UE's entity gets destroyed right after the UE goes back to idle mode; (ii) the UE's entity gets destroyed five minutes after the UE goes back to idle mode; and (iii) the UE's entity gets destroyed 10 min after the UE goes back to idle mode. Figure 24 shows the average, over nine days, of the ratio between the maximum number of active entities reached in cases (ii) and (iii) over the one reached in case (i). From the results in Figure 24, one can observe that: in case (ii), the maximum number of active entities in the network can be twice the number reached in case (i); in case (iii), the maximum number of active entities in the network can be three times the number reached in case (i). This means that, in case (ii), the maximum number of entities is roughly 20% of the user population, while it grows to about 30% in case (iii). Picking a threshold value sets a trade-off between entity restart rate and maximum number of active entities. A waiting time of 10 min would have a lower entity restart rate, but a quite large maximum number of active entities. A waiting time of five minutes, on the other hand, would still take care of most of the very short calls (as shown in Figure 23), while keeping the maximum number of concurrent entities active in the network anywhere between 9% and 18% of the user population. When to create and destroy VCNs, hence changing their number, is an optimization problem that, due to scalability, is critical to our new architecture. In order to study and estimate VCN scalability, we focused our analysis on voice-call traffic. In the future, we plan to enhance our traffic analysis with IP  
Figure 24: The ratio of active entities when destroying them after 10 and 5 min, over the baseline of destroying them right away, once UEs go back to idle mode. data traffic in order to estimate VCN scalability for non-voice data traffic and, in doing so, engineer a system optimized for all types of traffic.