# ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management
## 4 Performance Evaluations  
To evaluate the performance of the proposed scheme, we conducted experiments on various assumptions in which mobile users transmit computing tasks to access MECS and move to other access MECS. To do this, we implemented the network topology and MEC environments using CloudSim and Edge CloudSim, respectively [31; 32]. We built a virtual environment which resembles a university campus where the students walk around and request services from the access MECS located at the buildings on the specific area. We compared three different cases of mobile users' movement: (i) movement within the Zone; (ii) movement between Zones; and (iii) hybrid case moving inside and outside the Zone. The mobile users moved according to a nomadic mobility model in which they move to other access MECS after a random amount of time has passed [33; 34; 35]. In our simulation model, there were three location types with different mobile user preference levels. If the mobile user preference level of the access MECS was high, the mobile user was likely to spend more time in that access MECS. That is, the mobile user preference level of the location directly affected the dwell time that the mobile user spent in the related access MECS. The mobility model is illustrated in Figure 8 where \(\gamma\) is the dwell time and \(\beta_{ij}\) refers the probability of moving from the access MECS \(i\) to the access MECS \(j\). To express the complexity of the computing operation, we used million instructions per second (MIPS) to describe the ability to perform one million commands per second. In addition, we handled computation-intensive task and task migration of mobile users using containerization technology such as Docker, to handle tasks performed in simulation environments [36]. We assumed that each MECS could handle task migration requests of up to 300 mobile users. In Table 1, the important simulation parameters are listed. In Figure 9, the average service time is shown with regard to the average task size. We set the average task size as 500 million instructions (MI) and 3000 MI and the results are given in Figure 9a,b, respectively. Figure 9a shows average service time when task size is small. Since the proposed scheme manages access MECS as the concept of Zone, it is possible to provide a fast service even when the mobile user frequently moves to the inside or outside of the Zone. In addition, since the proposed scheme can migrate the tasks that are executed from the access MECS that the mobile user previously located using the information generated by the EMO and ZMO, it is possible to provide a fast service  
Figure 8: Mobility model used in the performance evaluation. even when the number of mobile users rapidly increases. However, if the task size is small, computing capability of the existing MEC environment can sufficiently process the task. Therefore, the proposed scheme has poor results compared to the existing MEC environment due to the overhead required for mobile user mobility support, but it is possible to provide a fast service without any problems. On the other hand, Figure 9b shows the average service time when task size is large. In the existing MEC environment, access MECS encounter with a computational resource congestion on VMs as the number of mobile users increases. Therefore, the average service time is increased due to the congestion as the number of mobile users increases. The proposed scheme manages access MECS as the concept of Zone and performs task migration from a previously located access MECS so it is possible to provide a fast service even when the number of users increases and the size of a task increases. In other words, the proposed scheme generates information for supporting the movement of mobile users by using EMO and ZMO and manages access MECS according to as the concept of Zone. Therefore, even when the mobile user frequently moves or the size of the task is large, it is possible to provide fast service.