# Integrating Multi-Access Edge Computing (MEC) into Open 5G Core
## 1 Introduction  
The fifth generation of networks (5G) is considered the main platform for future wireless applications, aiming to provide peak data rates of up to 20 Gb/s, average rates exceeding 100 Mb/s, and connectivity for a large number of Internet of Things (IoT) devices per unit area [1]. Additionally, reduced device battery usage, lower energy consumption, and the ability to connect an extremely high number of devices are also part of the objectives [2]. In the future, the 6G networks will continue to advance to manage growing data rate demands, increased numbers of instantiated slices, the densification of devices, and connected sensors [3]. This will require 6G to operate on a very large scale and in a hyper-connected and autonomous way, seeking to merge the digital and real worlds in all dimensions and ubiquitously, strongly integrating space and terrestrial networks, as well as making extensive usage of the location, sensing, and artificial intelligence technologies [4]. Recent studies in 6G networks highlight MEC as an essential enabler to be consolidated in 6G to fulfill the requirements of such dense network edges [3; 4; 5], e.g., MEC can guaranteeultra-low transmission delay and satisfy flawless 4k/8k video broadcast by processing computation-intensive data or caching ultra-high-definition (UHD) videos at the edge [3]. Standardized by 3 rd Generation Partnership Project (3 GPP), the 5G mobile network has various releases that define aspects of the network. One of these aspects is a new architecture that introduces separation between the Data Plane (DP) and Control Plane (CP) called SBA [6]. Additionally, a new generation of services has been proposed for 5G, including (i) eMBB: maximizing data transfer rates; (ii) URLLC: minimizing latency and ensuring high reliability; (iii) mMTC: supporting a large number of devices in the same area [7, 8]. The advent of 5G networks has opened up various possibilities for implementing new applications and services, such as virtual reality, augmented reality, autonomous vehicles, and IoT. These applications demand substantial network resources, requiring the network to support increasing data volumes. Features like ultra-low latency, wide bandwidth, and efficient resource consumption need to be delivered by a 5G network [9]. One effective approach is to deploy these applications at the network edge, bringing them closer to users and taking advantage of edge computing and reduced physical transmission times. This is where Multi-Access Edge Computing (MEC) becomes crucial [10]. Edge computing has emerged as a promising evolution of cloud computing, offering benefits such as improved scalability, particularly for large volumes of data, and lower latencies enabling critical real-time services like remote sensing and actuation or distributed gaming, as well as preserving privacy and contextual information [11]. MEC, standardized by the ETSI ISG, brings services closer to the data source at the network edge [12]. This standard encompasses a comprehensive framework and architecture [13]. Furthermore, there is a suite of MEC APIs designed in accordance with general principles of RESTful API design [14]. MEC is mostly accessed through mobile networks, such as 4G LTE-Advanced [15] and the growing 5G network [16], although it is access mode-neutral [11]. Rather than being a standalone solution, MEC is designed to complement 5G, particularly in addressing requirements such as ultra-low latency that are critical for URLLC [17]. In this context, the integration between 5G networks and MEC frameworks becomes essential and can be implemented through MEC services as defined by the ETSI reference architecture. Furthermore, carriers can leverage facilities at the edge of mobile networks, opening up the RAN to third parties, enabling flexible deployment of innovative services for mobile subscribers and businesses [11].