## 2 Related Work
As mentioned in [15], in the case of implementing the NFV concept, network energy consumption can be reduced by up to 50% compared to traditional telecommunications infrastructure. When it comes to mobile networks, the highest energy consumption occurs in the RAN part of the network (Table 1). This accounts for approximately 70% of the total system \begin{table}
\begin{tabular}{p{85.4 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Technology/Approach Enabling Network Slicing** & **Research Possibilities for EE Improvement** \\ \hline
[11] & SDN-based network slicing & Traffic-aware, end-host-aware, and rule-placement approaches using SDN scheduling \\ \hline
[12] & VNF-based network slicing & Virtual network functions’ scheduling \\ \hline
[1,3] & RAN-based network slicing & RAN resource scheduling \\ \hline
[4] & Network slicing based on the traffic’s adaptation to energy consumption patterns & Time-shift service execution of NS with possible QoS degradation and the power supply of NS derived from renewable energy sources \\ \hline
[13,14] & Ent-to-end (E2E) network slicing with stringent security requirements & NS scheduling through transport, the core, and the radio part of the network with guaranteed security requirements \\ \hline \hline \end{tabular}
\end{table} 
Table 1: An overview of research areas for improving energy efficiency through the implementation of 5G network slicing. energy consumption [1]. Therefore, different research efforts have aimed to improve the EE in the context of slicing the RAN part of the network. In [1], researchers propose a system for activating or deactivating RAN slices to establish a new slice with minimal activated resources and network elements, while maintaining a satisfactory QoS and low energy consumption. This approach can be realized in practice because slices are created for a specific type of traffic, service, or user, and can be deactivated when there is a significant reduction in the number of NS users and, consequently, NS traffic. However, the remaining active slice users need to be transitioned to the RAN elements of other active NSs. Deactivating the original slice increases overall network EE and the new slice to which users are migrated needs to use appropriate network resources to maintain the same or a slightly reduced QoS. For the allocation of resources in network slicing (Table 1), researchers in [3] proposed two algorithms to achieve Pareto boundaries for two key network parameters: throughput and transmit power. These two algorithms are based on utility profiles and scalarization approaches, and the numeric outcomes of this paper illustrate the benefits of concurrently assigning bandwidth and transmission power, while also showcasing how QoS criteria tailored to individual segments influence both data transfer rates and the overall EE. This specifically means that these algorithms can provide optimal resource allocation in network slicing from the perspective of throughput and EE. In [4], depending on the network services in NSs, strategies for managing EE to ensure its adaptability to the energy consumption patterns in 5G networks are presented (Table 1). This strategy suggests that network slices have priority identification that allows for normal service processing and the time-shift execution of services with a QoS degradation of some services or service rejection. The authors in [4] considered scenarios where energy is derived from renewable energy sources, meaning that a limited amount of energy is available, which makes it a limiting factor in service offerings. Therefore, the approach proposed in [4] cannot be applied to all types of slices, as some services are characterized by specific traffic activities, such as, for example, a service supporting autonomous vehicles. However, for slices enabling standard mobile services in 5G networks (such as voice, data, and video for commercial purposes, without excessive reliability requirements), the proposed strategies can be a significant step forward in terms of improving EE.