# Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies
## 3 Energy Management Proposal for 5G Network Slicing
### Architecture for Adaptive Energy Management  
#### 3.3.1 Architecture Description and Operation  
This section presents an architecture for adaptive energy management in 5G network slicing based on the established management and orchestration framework by the 3 GPP and ETSI [5; 6; 9]. This architecture is composed of two stakeholders, the customers and the MNO, as shown in Figure 2. The architectural framework is focused on the efficient energy resource management from renewable and non-renewable energy sources for the creation, configuration, and deployment of network slices and the corresponding services on the mobile network infrastructure. The architecture leverages the concepts of NFV and SDN as well as the IoT connectivity of customers to carry out the energy-aware realization of 5G network slices. From the operational perspective, the network slicing architecture can be considered to be comprised of two main blocks: (i) the first block is integrated with the NFV Management and Orchestration (MANO) framework and by 3 GPP Network Slice Management framework, as shown in Figure 2a), dedicated to the network slices management and configuration considering energy management requirements (optimization of power consumption); and (ii) the second block is composed by the NFV and SDN frameworks as well as by the underlying network resources dedicated to the network slice implementation. In the first block (MANO), with the information on customers (e.g., number of network slices and services, the power consumption of services, SST values, etc.) and the conditions on power generation (available from non-renewable and renewable energy sources), the MNO proceeds to create the network slice(s), starting from a base template, similar to the example shown in [34], or selecting a network slice profile from a network service catalog [7]. This template can be then customized to meet the specific requirement of the end users. To carry out the network slice(s) creation (by choosing any of the above methods) on the MANO framework, the MNO first analyzes the amount power demanded (consumed) for service processing (execution), considering the consumption in all segments of the mobile network (i.e., the power consumed in the core, transport, and access networks). This consumption estimation  
Figure 2: Overview of the architecture for adaptive energy management in 5G Network Slicing: (**a**) schematic of the proposed architecture; and (**b**) schematic of the network operator and management entities. procedure can be performed using historical data or predictive models; however, these issues are beyond the scope of this paper. The consumption estimation process is carried out for all services and for all network slices. It has two objectives: (i) estimate/verify if the available power (managed by the MNO) is sufficient to allow the processing of all services in all network slices; and (ii) establish the actions to be performed by the MNO to optimize power consumption (optimize the service processing). Traditionally, the increase in energy demand has been faced with the contracting or production of additional energy. However, this alternative involves an increase in OPEX and possible environmental impacts, and it is not a sustainable solution. In this regard, modern management systems demand adaptive consumption schemes restricted to availability and that prioritize the use of renewable energy, as described in Requirements R1, R4, and R5 in Section 3.1. Therefore, in the proposed architecture, the network slice process is aware of an available energy resource (i.e., services/slices and power supply considered jointly). The MNO if needed can apply various management strategies (detailed in Section 3.2) on services, which are deployed as algorithmic solutions on the Network Slice MANO (see Figure 2b) to adapt consumption to availability, optimize power consumption (avoiding peaks loads or energy shortage), and reduce dependence on non-renewable energy as much as possible.