## 4 Standardization of 5G Network Slicing Energy Efficiency KPIs
### Limiting Network Slice Energy Consumption  
One of the options for improving the energy efficiency of the 5G sliced network is an approach dedicated to limiting and reallocating the energy consumption of specific NS service(s) or complete NSs. The MNO can limit the maximum consumed energy for a particular NS or NS service(s). Figure 12a,c illustrate an example of an MNO energy consumption policy without energy consumption limitations for three services of one NS or three NSs, respectively. Figure 12: NSs energy consumption approaches based on: (**a**) no limitation on maximal energy consumption per NS service; (**b**) limitation on the energy consumption of NS services and scheduled energy consumption imposed by MNO; (**c**) no limitation on maximal energy consumption per NS; (**d**) limitation on NS energy consumption and scheduled energy consumption imposed by MNO. However, in case of limitations on overall NS(s) energy consumption being defined by the MNO, services can be realized through the degradation of the QoS to a minimally acceptable level for some services or NSs (Figure 12b,d). This energy-saving approach based on the degradation of QoS can be implemented in those services or NSs that do not demand high reliability, or have low traffic latency and can postpone the processing of data. Also, the QoS can be degraded for some services during a short period of time. However, if the degraded QoS persists, the QoS can become unacceptable and the maximum energy consumption threshold for specific service(s) or NS(s) should be adjusted by enabling the activation of additional network resources which will maintain an acceptable level of QoS. This leads to the necessity of developing techniques for the dynamic adaptation of the maximal energy consumption threshold for specific services or NSs according to the need to accommodate specific QoS standards of service or NS. In addition to service degradation and dynamic maximal energy consumption adaptation principles, it is possible to apply an algorithm for the temporal shifting of service execution or NS resource reallocation outside the time period of maximal energy consumption and complete execution of degraded service. Figure 12b,d illustrate a situation where limitations on the service or NS energy consumption were applied to service 2 or NS2, respectively, for the amount that exceeded the energy limitation. Also, Figure 12b,d present an example of a scenario where service 3 and NS3 had their execution and resources' reallocation temporally shifted in the periods outside of the maximal energy consumption threshold. This temporal shifting of the service execution approach can be implemented in practice, since users may be aware of the shifted service execution for specific services. This approach in turn can provide lower service costs to the users, as the MNO reduces expenses regarding energy consumption. Thus, the development of innovative algorithms for the temporal shifting of service execution or NS resource reallocation outside the time period of maximal energy consumption is also a possible way to optimize 5G networks' energy consumption. On the other hand, in practical implementations of NSs and corresponding services, there are services that should be prioritized in terms of execution. This can be achieved by the MNO, which will determine service or NS execution priorities, thereby deciding which of them takes precedence in terms of the usage of resources of the 5G network. However, prioritization of the execution of some services or the operation of NSs themselves may cause new limitations in terms of a lack of available energy in some parts of the 5G system, due to the increased energy consumption of resources needed for the realization of prioritized NS services or NSs. In that case, priorities can be set to determine which service or NS has an advantage in terms of energy consumption, and consequently in the usage of network resources.