# ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management
###### Abstract  
Recently, new mobile applications and services have appeared thanks to the rapid development of mobile devices and mobile network technology. Cloud computing has played an important role over the past decades, providing powerful computing capabilities and high-capacity storage space to efficiently deliver these mobile services to mobile users. Nevertheless, existing cloud computing delegates computing to a cloud server located at a relatively long distance, resulting in significant delays due to additional time to return processing results from a cloud server. These unnecessary delays are inconvenient for mobile users because they are not suitable for applications that require a real-time service environment. To cope with these problems, a new computing concept called Multi-Access Edge Computing (MEC) has emerged. Instead of sending all requests to the central cloud to handle mobile users' requests, the MEC brings computing power and storage resources to the edge of the mobile network. It enables the mobile user device to run the real-time applications that are sensitive to latency to meet the strict requirements. However, there is a lack of research on the efficient utilization of computing resources and mobility support when mobile users move in the MEC environment. In this paper, we propose the MEC-based mobility management scheme that arranges MEC server (MECS) as the concept of Zone so that mobile users can continue to receive content and use server resources efficiently even when they move. The results show that the proposed scheme reduce the average service delay compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because mobile users can continuously receive services, even when they move frequently. multi-access edge computing; multi-access edge computing mobility management 2019 9 2019  
However, due to constraints such as processing power and battery lifetime of mobile devices, mobile users cannot efficiently receive services that require high computing power and low-latency. To meet these service requirements, a computing paradigm is widely used to deliver these services to mobile users using cloud computing, such as Google Cloud Platform (GCP) and Amazon Elastic Compute Cloud (EC2) [10; 11]. With the computing paradigm of cloud computing and the development of many kinds of research, cloud computing could provide a well-established distribution model and application platform [12; 13]. Thanks to such computing paradigm, there are growing interests in powerful computing operations such as real-time online games and ultra-high definition (UHD) streaming that require very low latency and high access speeds [14; 15]. The existing cloud computing has performed computation-intensive tasks well with their powerful computing capabilities and scalability of cloud service infrastructure. The limitations are that cloud server is relatively remote for mobile users, making it unsuitable for services that require ultra-low latency and impossible to respond effectively in the event of the frequent mobile user movements. In addition, the massive volume of data exchanged between mobile users and remote cloud servers cause data tsunamis, leaving the backhaul network saturated. To solve these problems, various kinds of network architecture and methods are emerging [16; 17; 18]. Especially, a new network architecture, which places a small cloud with various computing functions close to the mobile user devices, is under active research named as Fog Computing and Multi-Access Edge Computing [19; 20; 21; 22]. Figure 1 shows the existing cloud computing architecture and MEC architecture. The concept of the initial Fog Computing was proposed by Cisco, which is a service infrastructure that provides data computation, storage, and application services similar to the cloud, but it does not perform the role of a central server and it does not feel like a central server [23; 24].