# Deep Learning at the Mobile Edge: Opportunities for 5G Networks
## 5 Standards towards 5G Automation
### Etsi  
ETSI is a European Standards Organization (ESO) that deals with electronic communications networks and services. It is a partner in the international Third Generation Partnership Project (3 GPP) and developed thousands of standards for mobile and Internet technology since 3G networks. With 3 GPP and the guidance of specialists in ISGs for NFV, mobile edge computing, and ENI, ETSIhas created standards to develop automated and cognitive services based on real-time user needs, local environmental conditions, and business goals [92; 93]. As researchers and technologists work to automate networks through DL, they must bear in mind the growing body of standards that will guide best practices for security, efficiency, and consumer experience in future networks. The main 5G management standard is ETSI's MANO (management and orchestration) architecture for NFV to simplify the roll-out of network services and reduce both deployment and operational costs. The three core functional blocks of MANO are:  
1. NFV Orchestrator that controls network services onboarding, lifecycle management, resource management including capacity planning, migration and fault management,
2. VNF Manager configures and coordinates of VNF instances, and
3. Virtualized Infrastructure Manager (VIM) that controls and manages the physical and virtual infrastructure, i.e., computing, storage, and network resources. Each functional block for MANO presents opportunities for meaningful DL implementations in highly virtualized 5G networks. The mobile edge computing and NFV architectures proposed by ETSI are complementary. Mobile edge computing and VNF applications can be instantiated on the same virtual infrastructure, in fact NFV sees the mobile edge computing as a VNF. The mobile edge computing consists of various entities that can be grouped into the mobile edge computing system level, the mobile edge computing host level, and networks. The mobile edge computing supports different network infrastructures including those proposed by 3 GPP for 5G in particular. Mobile edge computing can be one of the cornerstones of 5G at the edge. The 5G system designed by 3 GPP makes it easier to deploy user plane functions on the edge of 5G network. The Network Exposure Function (NEF) in the Control Plane shows the capabilities of network functions to external entities. One of the features supported by the mobile edge computing is 5 GcoreConnect, which interchanges notifications between the 5G Network Exposure Function in the control plane or other 5G core network function. This feature allows the mobile edge computing to receive or send traffic, change the routing policy, or perform policy control. Mobile edge computing can use the shared information for application instantiation to manage the selected mobile edge computing host, select the mobile edge computing host, or perform various functionalities between both systems. ETSI ISG mobile edge computing is focused on the management domain, some of its use cases being cognitive assistance, optimization of QoE and resource use or smart reallocation of instances, among others. The strict features of these use cases make a standardization framework essential for the application of ML in domain management. To continue progress in connecting mobile edge computing and DL implementations for 5G, ETSI's ENI has developed models in which machine learning techniques can replace manual orchestration or traditional static policies in MANO architecture [94]. Use cases identified by ENI align with the goals in 5G research currently, and if properly realized, can even address some open issues discussed in Section 4, such as security and energy usage. ENI functional blocks include knowledge representation and management, context-aware management, situational-aware management, policy-based management, and cognition management. Using these functional blocks, 5G networks can apply the fundamentals of zero-touch network and service management (ZSM) to become self-configuring, self-optimizing, and self-healing.