# Cloud-Enabled Deployment of 5G Core Network with Analytics Features
## 3 Background
### Virtualization of a 5G Core Network
In the event of an NF failure, only a limited subset of services becomes unavailable until the affected NF is recovered. To achieve granularity and scalability, 5 GCNs employ a new approach for interactions between core components. Service-Based Architecture (SBA) defines a model in which a set of network functions provides services to other eligible NFs. This can be represented as a reference-point view, where a reference point signifies point-to-point links between NFs that exchange services [30]. Alternatively, SBA can be represented through a service-based representation, in which network functions are interconnected by the services they provide. This representation is applicable only to the control plane (CP). The interfaces between the CP and the user plane (UP) are implemented via reference points (e.g., the interface between the User Plane Function (UPF) and the Session Management Function (SMF) [21]). SBA is commonly implemented using service-based representation, as reference-point interfaces are replaced with corresponding Service-Based Interfaces (SBIs) wherever possible. Figure 1 illustrates the architecture of the 5 GCN. The Network Exposure Function, as defined in 3 GPP 23.501 [21], provides external exposure of CP NFs' capabilities to third-party applications. This functionality can be particularly advantageous for 5G cloud-based deployments in a virtualized environment that supports network slicing. However, NEF is not included in the most popular open-source implementations of the 5 GCN. Moreover, many unimplemented network functions are based on NEF. Therefore, we decided to design and develop a network function that mirrors the functionalities of NEF to benefit the community of researchers and developers focused on applications utilizing 5G networks. Mobile network operators expect NEF to provide internal data from the 5G core for broad analysis. This analysis, based on live on-demand data from the network, would be used to anticipate undesired events, such as overloads and service request rejections. Slicewise data can be valuable for predicting the resources required to ensure uninterrupted service provisioning. For instance, summary data showing the total aggregated maximum bitrate for a given Data Network (DN) may indicate the need to increase the number of UPF instances in the user plane to alleviate the utilization of existing NFs [31]. If the 5 GCN control plane needs to be scaled, information about the Session and Service Continuities (SSCs) supported by UEs for a specific DN can help ensure PDU session continuity as the generated traffic is offloaded onto newly deployed UPFs. Additionally, the total bitrate per DN may be a critical factor when adjusting virtualized resources to the state of the network, enabling efficient cloud-based deployment [32]. If the 5 GCN infrastructure is  
Figure 1: Architecture of the 5G Core Network, highlighting the main network functions. at risk of overload, additional network resources must be deployed [33]. It is essential to reduce pressure on physical hardware to ensure the continuous delivery of critical 5G services. However, physical constraints may limit the deployment of additional NFs on a given platform. In such cases, the last resort may be to release a subset of non-critical services, such as low-priority PDU sessions, to reduce the load on the network.