# Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies
## 1 Introduction  
### Background and Motivation  
The deployment of 5G mobile networks introduces new services and applications to facilitate a wide range of end user demands. However, before these innovations can be made available to customers and vertical markets, some challenges need to be addressed, such as the efficient management of network resources, multi-tenancy approaches, and the management of energy consumption [1; 2]. Regarding the first two points, network slicing architecture has emerged as a means to efficiently support dynamic resource management in a multi-tenant environment [3]. Specifically, network slicing for 5G mobile communications leverages on the concepts of Network Functions Virtualization (NFV) and Software Defined Networking (SDN) to implement multiple virtual and independent logical networks, referred to as network slices, on a common shared physical network infrastructure [4; 5]. In network slicing, each slice (virtual network) is an isolated amount of end-to-end network resources and functions with different requirements, including energy, and with independent management and control, tailored to fulfill the diverse demands requested by a particular operator, application, service, customer, or vertical market [6]. The Mobile Network Operator (MNO) can configure and manage the control plane and user plane network functions and the corresponding resources (e.g., access, transport, and core networks) to support various Slice/Service Types (SST) [7]. These SST can be grouped according to their different requirements in functionality (e.g., priority, charging, security, and mobility), on performance requirements (e.g., reliability, latency, mobility, and data rate), or they can be targeted to specific users (e.g., public safety users, corporate customers, or virtual operators) [2]. In the technical specification TS 23.501 v16.4.0 (issued in March 2020), the 3 rd Generation Partnership Project (3 GPP) provides a standardized classification that groups different services, such as enhanced Mobile Broadband (eMBB) services, Ultra-Reliable Low-Latency Communications (URLLC) services, massive Internet of Things (IoT) services (MIoT), and Vehicular-to-everything communications (V2X, where the X means vehicle, infrastructure, pedestrians, etc. ), within four SST categories [1], as shown in Table 1. This classification can be used as a baseline or template to implement network slices for most customer requirements. In addition, the TS 23.501 v16.4.0 does not limit the creation of other categories if necessary, and the assigned SST values do not give priority to one category over the others. Regarding energy consumption management, this feature is a key factor in the deployment and evolution of mobile networks [8], and it is also a crucial consideration for the following reasons: (i) constant growth in energy consumption because of the increasing number of devices connected to mobile networks and the corresponding network densification from the deployment of a high number base stations and related infrastructures (legacy networks 2G, 3G, and 4G must coexist with 5G and beyond networks) [9]; (ii) increased traffic demand and heterogeneity of services with different requirements (e.g., high data rate, low latency, wide bandwidth, a high operating frequency of up to 60 GHz, reliability, or connectivity) [10]; (iii) increase in the Operation Expenditures (OPEX) for the MNO, because, more energy consumption means more costs of energy supply, which can produce an impact on tariffs for consumers or less margins for the operators [8]; and (iv) sustainability issues, which call for new energy generation and consumption principles [10]. Historically, the evolution of mobile networks has implied an increase in energy consumption. However, this current reality needs to change due to sustainability considerations, the increase in CO\({}_{2}\) emissions, and the impact on climate change caused by the use of fossil fuels for energy production (e.g., electricity) [11].