# Hierarchical Mobile Edge Computing Architecture Based on Context Awareness
## 1 Introduction  
With the explosion of mobile and Internet of Things (IoT) devices and the evolution of mobile networks, a variety of services that require low latency and high speed are emerging. To provide services that meet these requirements, cloud computing services, such as Dropbox, Google Cloud Platform, and Amazon, have emerged. Also, with the development of many studies and technologies related to cloud computing, cloud computing could provide a well established distribution model and application platform. Thanks to the computing paradigm, there is growing interest in new applications and services. For example, there are real-time online games, powerful computing operations like machine learning and ultra-high definition (UHD) streaming that requires very low latency and high access speeds. In the meantime, due to the need for high computing power by such services, the cloud computing platform has been considered as a solution to handle such services. Figure 1 shows the existing cloud computing environment. Even though existing cloud computing platforms have performed well, computation-intensive services with their powerful computing capabilities have trouble, and they cannot efficiently use cloud computing resources because there is no consideration of situations requiring ultra-low latency and high computing performance. Furthermore, the enormous amount of data exchanged between user devices and remote cloud servers causes a data tsunami, which leads to saturation and brings down the back-haul networks. In order to solve such problems, new network architectures, named Fog Computing and Mobile Edge Computing (MEC), which place a small cloud with various computing functions close to the user devices, are under active research [1; 2; 3; 4; 5]. The initial concept of Fog Computing was proposed by Cisco, which is a service infrastructure that accesses the computation and storage resources of network equipment. This service provides data computation, storage, and application services, like the cloud, but it does not feel like a central server. That is, Fog Computing seamlessly extends cloud computing to the edge for the secure control and management of domain specific hardware, software, storage, and network functions within the domain and enables secure rich data processing applications across the domain. Similarly, the concept of MEC [6] was proposed by the European Telecommunications Standard Institute (ETSI) and is defined as a new platform that provides IT and cloud computing capabilities within a radio access network (RAN) in close proximity to mobile users. In other words, MEC, which is considered a promising and emerging paradigm for the provision of powerful computing capabilities in proximity to mobile devices in 5G networks, enables fast and popular content delivery of delay-sensitive applications at the back-haul capacity of limited mobile networks. In this paper, we focus on a proposed hierarchical architecture based on the MEC environment. Although many studies on the MEC environment have been conducted, existing works have little regard for the efficient arrangement and structure between the central cloud server and the MEC server (MECS) [7; 8; 9; 10]. In addition, there is a problem in that MECS and cloud computing resources cannot be efficiently used due to insufficient consideration of operations specific to the content and computing operation types in the MEC environment; thus, the user service is delayed. So, this paper proposes an architecture that enables users to provide low-latency services and efficient use of server resources by hierarchically arranging MECS specialized for content type and computing operation type. The basic idea of the proposed architecture is to efficiently utilize resources of MECS and to provide users with services specific to their content type and computing type based on operations through a hierarchical MECS configuration with service profile information. The rest of the paper is organized as followed.