# On End-to-End Intelligent Automation of 6G Networks
## 3 5G Orchestration: Related Works and Limitations
### Limitations  
Many of the previous works on 5G network orchestration that have been previously proposed in the literature and developed by the industry suffer from multiple limitations/shortcomings. In what follows, a brief discussion of these limitations/shortcomings is presented.  
1. **Centralized Orchestration:** One main shortcoming in current 5G network orchestration frameworks is their centralized nature. Most current frameworks do not extend  
\begin{table}
\begin{tabular}{c c} \hline \hline
**5G Orchestration Technique** & **List of Previous Efforts** \\ \hline Mathematical Optimization-Based Solutions & [75; 77; 79; 80] \\ \hline Game-Based Solutions & [76; 77] \\ \hline Metaheuristic-Based Solutions & [78; 80] \\ \hline Heuristic-Based Solutions & [70; 71; 73; 74; 75] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of previous efforts—5G orchestration methodology.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**5G Orchestration Level** & **List of Previous Efforts** \\ \hline Core Level & [70; 76; 77; 80] \\ \hline Transport Network Level & [71; 73; 75] \\ \hline Radio Access Network Level & [71; 74; 79] \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of previous efforts—5G orchestration level.  
to the extreme edge. More specifically, the current orchestration solutions rely on ETSI's NFV MANO framework [81; 82]. This framework is typically deployed in a centralized location. This is a major limitation, particularly as it may represent a single point-of-failure and cause significant congestion at the core network level. Hence, using it as the basis of current 5G orchestration solutions is a significant concern.
2. **Single-Layer Orchestration**: Another limitation facing 5G orchestration frameworks is that they often only focus on orchestrating at one particular level. For example, the focus can be only on the radio level, transport level, or core level [83]. This is highlighted by the related works summarized above, in which the focus was often on orchestrating one type/level of the network. The problem lies in the fact that orchestrating at one level only may not result in the optimal allocation and utilization of all the available resources, particularly given that the resources at the different levels of the network are dependent and have a direct impact on the overall performance of the network. As such, current orchestration frameworks are limited in their ability to provide optimal orchestration decisions across the different levels of the network.
3. **Limited AI/ML-Enabled Orchestration**: A third limitation of current orchestration frameworks proposed for 5G networks is their limited use of AI and ML technologies. Although such technologies are being proposed in current 5G network deployments [84; 85], this is being done in a limited manner and only at specific levels within the network. This is partially due to the absence of real-world datasets that can be used to develop such AI/ML-enabled orchestration frameworks. As a result, these technologies are not being utilized to their full potential despite the fact that a large amount of important and relevant data can be collected by the different entities within the network. Consequently, this limits 5G networks' ability to truly become \"zero-touch\" networks (i.e., networks capable of self-configuration, self-monitoring, self-healing, and self-optimization [86]).