Provisioning of network energy management in communication systems

Abstract

Embodiments of this disclosure relate to the provisioning of network energy management in a communication system. According to embodiments, the device may include an energy management function (EMF) for a communication network. The device may be configured to execute instructions to implement the EMF, which includes receiving one or more energy data related to at least one network entity from at least one network entity; processing one or more energy data to generate an energy efficiency level related to at least one network entity; and performing one or more operations to manage the energy use of at least one network entity based on the energy efficiency level.

Description

Technical Field

[0001] [Cross - reference to Related Applications] This application claims priority from Indian Provisional Patent Application No. 202341037534, filed with the Indian Patent Office on May 31, 2023, entitled "Network Energy Management in 5G Architecture", the entire disclosure of which is incorporated herein by reference.

[0002] [Technical Field] Embodiments of the present disclosure relate to the provisioning of network energy management in one or more communication systems.

Background Art

[0003] The information and communication technology (ICT) industry is a representative of important energy consumers worldwide. Along with the progress and evolution of communication systems such as communication systems, the operation of communication systems is theoretically and ideally designed to achieve improved energy efficiency and reduce energy consumption. Nevertheless, with the rapid commercialization of advanced communication systems (such as 5G systems, etc.) worldwide, the number of devices, equipment, etc. related to communication systems has increased significantly. As a result, the rapid increase in the density of network entities and network traffic is expected to offset the energy - saving capabilities provided by advanced communication technologies and lead to a net increase in energy consumption in communication systems.

[0004] For example, 5G network systems are dynamic systems that continuously consume energy and respond to spikes in network activity. Specifically, a large portion of the energy may be consumed by radio access network (RAN) components such as antennas, radio units, and base station elements. Each component may have a denser infrastructure in today's infrastructure, facilitate support for increased traffic, operate across more frequency bands, and increase the power consumption of base stations. Typically, RAN elements such as massive MIMO (Multiple-Input Multiple-Output) antennas and beamforming shift and concentrate power consumption in 5G systems. Thus, massive MIMO antenna arrays require additional power per sector and also impact the energy consumption of the RAN. Furthermore, the adoption of edge computing and widespread IoT (Internet of Things) has made increased energy consumption inevitable. In addition, core computing, analytics, and storage contribute to the increased energy consumption of 5G networks. [Overview of the project] [Problems that the invention aims to solve]

[0005] In light of the above, the increasing energy consumption in telecommunications networks has heightened the importance of energy saving for operators and service providers who already allocate a large portion of their OPEX (Operational Expense) budget to power.

[0006] The embodiments of this disclosure efficiently and effectively facilitate the provisioning of energy management in one or more communication systems. [Means for solving the problem]

[0007] According to one embodiment, the device may include an energy management function (EMF) for a communication network. The device may be configured to execute instructions to implement the EMF, which includes receiving one or more energy data related to at least one network entity from at least one network entity; processing one or more energy data to generate an energy efficiency level related to at least one network entity; and performing one or more operations to manage the energy use of at least one network entity based on the energy efficiency level.

[0008] According to embodiments, the method may include receiving one or more energy data from at least one network entity and relating to at least one network entity; processing one or more energy data to generate an energy efficiency level relating to at least one network entity; and performing one or more operations to manage the energy use of at least one network entity based on the energy efficiency level. The method is implemented by an Energy Management Function (EMF) for a communications network.

[0009] According to one embodiment, a non-temporary computer-readable recording medium may record instructions for implementing an energy management function (EMF) for a communication network. The instructions may be executable by the device to cause the device to perform a method comprising: receiving one or more energy data related to at least one network entity from at least one network entity; processing one or more energy data to generate an energy efficiency level related to at least one network entity; and performing one or more operations to manage the energy use of at least one network entity based on the energy efficiency level.

[0010] Additional aspects may be partially presented in the following description, partially revealed from the description, or realized by implementing the embodiments presented in this disclosure. [Brief explanation of the drawing]

[0011] Features, advantages, and importance of exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, where similar reference numerals represent similar elements.

[0012] Figure 1 illustrates a block diagram of a system architecture for provisioning network energy management in a communication system according to one or more embodiments.

[0013] Figure 2 illustrates a block diagram of an example of a system configuration for implementing an energy management function (EMF) according to one or more embodiments.

[0014] Figure 3 illustrates a block diagram of another example of a system configuration for implementing EMF according to one or more embodiments.

[0015] Figure 4 illustrates an example of an environment in which the EMF, related systems, and / or methods described herein may be implemented.

[0016] Figure 5 illustrates a block diagram of an example of components of a container-based server node according to one or more embodiments.

[0017] Figure 6 illustrates a block diagram of an example of components of a server node according to one or more embodiments.

[0018] Figure 7 illustrates a diagram of an example of a configuration of an example of components of a server node according to one or more embodiments.

[0019] Figure 8 illustrates a flowchart of an example of a method for provisioning network energy management according to one or more embodiments.

[0020] Figure 9 illustrates a block diagram of an example of a system configuration related to a first use case according to one or more embodiments.

[0021] Figure 10 illustrates a block diagram of an example of a system configuration related to a second use case according to one or more embodiments.

[0022] Figure 11 illustrates a block diagram of an example of a system configuration related to a third use case according to one or more embodiments.

[0023] Figure 12 illustrates a block diagram of an example of a system configuration related to a fourth use case according to one or more embodiments.

[0024] Figure 13 illustrates a block diagram of an example of a reference point presentation of a network system in which EMF is implemented according to one or more embodiments.

Best Mode for Carrying Out the Invention

[0025] [[ID=4

[0026] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the exact forms disclosed. Changes and modifications are possible in light of the foregoing disclosure or may be derived from practice of the implementation. Additionally, one or more features or components of one embodiment may be integrated with or combined with those of other embodiments (or one or more features of other embodiments). Further, in the operation descriptions provided below, one or more operations may be omitted, one or more operations may be added, one or more operations may be executed simultaneously (at least partially), and the order of one or more operations may be interchanged.

[0027] It will be apparent that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual special control hardware or software code used to implement these systems and / or methods is not limiting. For this reason, the operations and behaviors of the systems and / or methods are described herein without reference to specific software code. It is understood that software and hardware may be designed to implement the systems and / or methods based on the descriptions herein.

[0028] [[ID=**10**]] Even if certain combinations of features are disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically disclosed in the specification.

[0029] None of the elements, actions, or commands used herein should be interpreted as important or essential unless explicitly stated otherwise. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." When only one item is intended, the term "one" or similar is used. Also, as used herein, the terms "has," "have," "having," "include," "including," etc., are intended to be open-ended terms. Furthermore, the phrase "based on" means "at least partially based on" unless explicitly stated otherwise. Furthermore, expressions such as "at least one of A and B," "at least one of A or B," or "A and / or B" are understood to include only A, only B, or both A and B.

[0030] Furthermore, since the terms "communication system," "network system," and "communication network system" described herein refer to the same element, it can be understood that these terms may be used interchangeably here.

[0031] For the sake of clarity, this disclosure may include terms and names defined by one or more standardization bodies, such as the 3GPP (3rd Generation Partnership Project) and the ETSI (European Telecommunications Standards Institute). For example, the terms "service-based architecture," "service-based interface," "service level agreement (SLA) standard," "non-public network (NPN)," "private network," "network slice," and "data network" are interpreted as being defined by 3GPP standards, etc.

[0032] Furthermore, terms such as “energy management,” “network energy management,” and “network energy consumption management” used herein refer to the process of performing one or more operations to manage the energy use of one or more network entities in order to ensure energy efficiency in a communication system. More specifically, the terms may refer to the process of effectively managing the energy consumption of one or more network entities in a communication system in an optimal manner in order to provide the same service that could be provided using less efficient methods. In general, energy efficiency optimization may refer to the practice of reducing energy consumption and / or energy requirements while providing services in an efficient or optimal manner. Thus, one or more network resources utilized by network entities may be dynamically adapted to efficiently manage energy in a communication system.

[0033] In related technologies' communication networks, there are no defined and supported energy efficiency standards as part of standardized communication services for users and application services. In other words, specific methods for optimizing energy efficiency in advanced communication network systems (e.g., 5G, 6G, etc.) remain undefined and unestablished to this day. In light of the above, there is a need for defined system architectures and approaches for provisioning energy management in communication network systems in order to optimize their energy efficiency.

[0034] Embodiments of this disclosure provide system architectures, system configurations, and procedures for efficiently and effectively facilitating the provisioning of network energy management in one or more communication systems.

[0035] According to embodiments, a system architecture for implementing energy management functions is provided. Specifically, embodiments of the present disclosure provide a device, such as a server node, that hosts a dedicated energy management function (EMF) for a communication network (which may be referred to as the “Network Energy Saving Function,” “NESF,” “Energy Saving Function,” “ESF,” or any other appropriate term). The device (e.g., a server node) may execute the EMF (or computer-readable instructions for implementing the EMF) to perform one or more operations for provisioning network energy management. For example, when executing instructions for implementing the EMF, the device (e.g., a server node) may be configured to: acquire one or more energy data for one or more network entities (e.g., via the infrastructure of a communication system); process one or more energy data to acquire useful energy information (e.g., energy consumption of one or more network entities, energy efficiency levels of one or more energy entities, etc.); and perform one or more operations to manage the energy use of one or more network entities based on the energy information. An example description of a system architecture for implementing the EMF is provided below with reference to Figure 1.

[0036] Since the implementation of EMF in the embodiments of this disclosure utilizes the infrastructure of a communication system, existing network infrastructure may be used, and the cost of implementing and providing network energy management may be minimized. Furthermore, the time required for developing and rolling out new related services may be reduced.

[0037] According to one embodiment, an EMF may be used by a device (e.g., a server node) to interact with one or more network functions (which may be referred to here as "core network functions") of the core network of a communication system. The EMF may be hosted or deployed on a server node near the component where one or more network functions are deployed, which are typically servers in a regional data center or servers in a central data center. In this case, the EMF may be deployed as a core network function.

[0038] Alternatively, the EMF may be hosted or deployed on a server near the end user and / or network infrastructure where energy is supplied, consumed, and regulated. Since such a server may be located in an edge data center, the server may be referred to here as an “edge server.” A description of an example system configuration for implementing the EMF is provided below with reference to Figures 2 and 3.

[0039] Embodiments of the present disclosure may enable interaction and interoperation between a device (which deploys and utilizes an EMF) and a core network function, and may enable efficient communication of energy data and energy information to optimize the energy efficiency of the core network function, and may enable the core network function to utilize the energy information to manage its energy use.

[0040] According to the embodiments, EMF may be hosted or deployed in a cloud server or cloud computing environment. A description of an example environment in which EMF may be implemented is provided below with reference to Figure 4. Furthermore, EMF may be containerized and deployed in a container-based server. Thus, the implementation of EMF in the embodiments of this disclosure may take advantage of the benefits of containerization, such as high scalability, reliability, portability, and resource efficiency. A description of an example device (e.g., a server node) in which EMF may be implemented is provided below with reference to Figures 5 to 7. Furthermore, a description of an example operation that may be performed by the device (e.g., a server node) is provided below with reference to Figure 8, and a description of an example use case related thereto is provided below with reference to Figures 9 to 12.

[0041] According to the embodiments, an implementation of EMF relating to reference point representations is provided. Specifically, the embodiments of the present disclosure introduce at least three novel reference point representations, each of which may be used to communicate with its respective network function. The introduction of these novel reference points not only ensures effective integration into the communication system and implementation of EMF, but also defines extensive interactions with key network functions. Thus, EMF may be used by server nodes to manage the energy consumption of network entities across the network system and optimize energy efficiency across the entire network system.

[0042] Ultimately, embodiments of this disclosure provide system architectures, system configurations, and operations for implementing and utilizing energy management functions in a communication system, enabling the effective and efficient management of energy consumption of network entities in the communication system and optimizing the energy efficiency of the communication system.

[0043] The features, advantages, and importance of the embodiments described herein are only a part of this disclosure and are not intended to be exhaustive or to limit the scope of this disclosure.

[0044] Further description of the features, components, configuration, operation, implementation, and related technical advantages of the embodiments of this disclosure is provided below.

[0045] [Overall System Architecture] Figure 1 illustrates a block diagram of a system architecture 100 for provisioning network energy management in a communication system according to one or more embodiments.

[0046] As illustrated in Figure 1, the system architecture 100 may include at least one server node 110 and a plurality of network entities 120. The at least one server node 110 may be a device, apparatus, or apparatus configured to house, host, deploy, and / or utilize at least one energy management function (EMF) 110-1, and may be communicatively coupled to the plurality of network entities 120. The plurality of network entities 120 may include at least one network function 120-1, at least one user equipment (UE) 120-2, at least one access network (AN) 120-3, and any other suitable devices, apparatus, or systems that may contribute to the energy consumption of the communication system. Generally, the server node 110 may be configured to execute EMF 110-1 (or instructions for implementing EMF 110-1) to provide and perform energy management for at least one of the plurality of network entities 120.

[0047] At least one server node 110 may include one or more devices such as one or more servers, which may include one or more components (e.g., storage) configured to store or host at least one EMF110-1, and may have one or more components (e.g., processors) configured to run or utilize at least one EMF110-1 to manage (e.g., receive, store, process, execute, etc.) energy-related information, data, tasks, and operations. A description of examples of components that may be included in the server node 110 is provided below with reference to Figures 6 and 7, and a description of examples of operations that may be performed by the server node is provided below with reference to Figures 8 to 12.

[0048] According to the embodiment, at least one server node 110 may include one or more edge servers (which may be referred to here as “edge nodes”), where the server is deployed or implemented in one or more edge data centers located near a target entity or device, rather than in a central data center. For example, the server node 110 may be located or deployed in one or more edge data centers near the server node where the network function 120-1 is deployed, such as near UE120-1 or AN120-3. By implementing the server node 110 (and the EMF110-1 contained therein) at the edge, energy management may be performed with reduced latency, reducing the energy consumption required to perform energy management and minimizing the impact of energy management operations on the energy efficiency of the network system.

[0049] The Energy Management Function (EMF) 110-1 (which may also be described as Network Energy Saving Function (NESF), Energy Saving Function (ESF), or any other appropriate term) may represent a dedicated network function for a communications network and may be responsible for managing energy-related data, information, tasks, and operations within the communications network. Furthermore, EMF 110-1 may be deployed as a core network function of the communications network. EMF 110-1 may be defined in a software-based form, such as a computer executable instruction, algorithm, or software application program. In addition or alternatively, EMF 110-1 may be defined in the form of a virtualized network function (vNF), an element of software-defined networking (SDN), etc.

[0050] By introducing and implementing EMF110-1 on server node 110, energy management functions, operations, and algorithms may be virtualized or defined in software form, and may be isolated and implemented on different nodes that may be located in different locations. According to the embodiment, EMF110-1 (or instructions for implementing EMF110-1) may be hosted, deployed, or implemented on a cloud server or cloud server cluster such as a hybrid cloud server / hybrid cloud cluster.

[0051] Alternatively, or in addition, EMF110-1 may be containerized, hosted, deployed, or implemented in the form of containers, pods, and / or microservices on a server or platform based on one or more containers. For example, server node 110 may include one or more container-based nodes (e.g., Kubernetes (K8s) nodes), and EMF110-1 may be isolated and distributed across multiple containers, for example, according to the operations and functions of EMF110-1. By deploying EMF110-1 as a containerized application, the advantages of containerization, such as high portability, scalability, and resource efficiency, can be utilized in the implementation of EMF110-1.

[0052] In some embodiments, the server node 110 may be configured to utilize the EMF 110-1 in conjunction with one or more additional network functions (e.g., network function 120-1). For example, the server node 110 may be configured to store / host the one or more additional network functions and / or to interact with one or more devices / nodes hosting the one or more additional network functions as needed (more on network function 120-1 below). In some embodiments, the EMF may subscribe to one or more operation, administration, and maintenance (OAM) tools and communicate with one or more OAM tools to obtain energy-related data from there.

[0053] According to the embodiment, the functions of EMF110-1 may be separated into multiple categories according to the network function. For example, the functions of EMF110-1 may be separated into a first category related to a first network function, and may also include a second category related to a second network function.

[0054] In some embodiments, the server node 110 may include multiple server nodes, and the EMF110-1 may be hosted or deployed on multiple server nodes. In this regard, the EMF110-1 may be hosted or deployed on multiple server nodes, for example, according to functional categories. For example, the first part of the EMF110-1 related to the first part of network functionality may be hosted or deployed on the first server node 110, and the second part of the EMF110-1 related to the second part of network functionality may be hosted or deployed on the second server node 110. In some implementations, the first part of the EMF110-1 may be hosted or deployed on an edge server, and the second part of the EMF110-1 may be hosted or deployed on a central server.

[0055] Furthermore, the EMF110-1 may be hosted or deployed on multiple server nodes according to their respective functions. For example, a portion of the EMF110-1 related to data computation operations may be hosted on a first portion of multiple server nodes, while other portions of the EMF110-1 related to energy management operations may be hosted on a second portion of multiple server nodes.

[0056] In light of the above, virtualizing the energy management function to EMF110-1 and separating the functions of EMF110-1 enables energy management to be implemented, configured, and delivered dynamically and flexibly according to different network configurations and / or network requirements, while simultaneously enabling centralized management of energy-related data, tasks, and information. As a result, energy management can be implemented and delivered easily, flexibly, and optimally.

[0057] Still referring to Figure 1, the network entity 120 may include one or more network functions 120-1, which the server node 110 may utilize EMF 110-1 for interoperability. One or more network functions 120-1 may include one or more network functions of the core network of a communication system, such as an LTE EPC (evolved packet core) network, a 5G core network, or a 6G core network. According to the embodiment, in addition to one or more network functions 120-1, EMF 110-1 may be deployed as a core network function of the communication network.

[0058] As a non-limiting example, one or more network functions 120-1 may include one or more of the following: Access and Mobility Management Function (AMF), Session Management Function (SMF), Network Data Analysis Function (NWDAF), Network Repository Function (NRF), Network Exposure Function (NEF), User Plane Function (UPF), Policy Control Function (PCF), Unified Data Management (UDM), Application Function (AF), Network Slice Selection Function (NSSF), Network Slice-Specific Authentication and Authorization Function (NSSAAF), Authentication Server Function (AUSF), Policy Control Function (PCF), Unified Data Management (UDM), Service Communication Proxy (SCP), Network Slice Admission Control Function (NSACF), and Edge Application Server Discovery Function (EASDF). One or more of the above network functions may be defined by one or more features and / or requirements specified in one or more specifications provided by the 3GPP standardization body, or may be compatible with such one or more features and / or requirements. One or more network functions 120-1 may be understood to further include any other suitable network functions defined or specified in one or more specifications provided by one or more standardization bodies (e.g., 3GPP, ETSI, etc.) without departing from the scope of this disclosure.

[0059] Each of the above network functions may be coupled to the EMF110-1 for communication via its respective dedicated interface. For example, in a service-based architecture (SBA), each of the network functions may expose its respective function (e.g., network capabilities, resources, information, etc.) via a dedicated service-based interface (SBI). For example, AMF may expose its function via the Namf interface, SMF may expose its function via the Nsmf interface, NWDAF may expose its function via the Nnwdaf interface, NRF may expose its function via the Nnrf interface, NEF may expose its function via the Nnef interface, PCF may expose its function via the Npcf interface, UDM may expose its function via the Nudm interface, AF may expose its function via the Naf interface, NSSF may... Functions may be exposed via the Nnssf interface, NSSAAF may be exposed via the Nnssaaf interface, AUSF may be exposed via the Nausf interface, PCF may be exposed via the Npcf interface, UDM may be exposed via the Nudm interface, SCP may be exposed via the NscP interface, NSACF may be exposed via the Nnsacf interface, and EASDF may be exposed via the Neasdf interface.

[0060] In this regard, the embodiments of the present disclosure provide a dedicated SBI "Nemf" to expose the functionality of the EMF110-1 to network entities in a communication system. Through the Nemf interface, the EMF110-1 may communicate with and interact with other network functions.

[0061] In addition to SBI, some network entities may communicate via interfaces defined by reference point representations. For example, an AMF may communicate with UE120-2 via the N1 interface, an AMF may communicate with AN120-3 (e.g., gNodeB, etc.) via the N2 interface, an AN may communicate with a UPF via the N3 interface, an SMF may communicate with a UPF via the N4 interface, a UPF may communicate with a data network (DN) (e.g., any other external or internal network or service platform such as the Internet, a public cloud, or a private cloud) via the N6 interface, and multiple UPFs (e.g., an intermediate I-UPF and a UPF session anchor, etc.) may communicate with each other via the N9 interface. As further described below with reference to Figure 13, embodiments of the present disclosure provide at least three new interfaces (i.e., "N110", "N111", "N112") defined by reference point representations to connect EMF110-1 to other network entities in a communicable manner.

[0062] Still referring to Figure 1, the network entity 120 may include at least one user equipment (UE) 120-2. The UE 120-2 may include one or more pieces of equipment, devices, etc., which may be used by one or more network users (e.g., end users such as network operators and network subscribers) to access the network system through interaction with other network entities. For example, the UE 120-2 may include one or more computing devices (e.g., desktop computers, laptop computers, tablet computers, handheld computers, smart devices, servers, etc.), mobile phones (e.g., smartphones, wireless phones, etc.), wearable devices (e.g., a pair of smart glasses or a smartwatch), SIM-based devices, and / or any other suitable devices or equipment. According to the embodiment, the UE 120-2 may include a 3GPP-based UE which is configured to emit and transmit one or more signals in the form of 3GPP radio signals and / or via one or more 3GPP interfaces.

[0063] Furthermore, the network entity 120 may include at least one access network (AN) 120-3. The AN 120-3 may include a radio access network (RAN) which may include at least one base station (e.g., eNodeB, gNodeB, etc.), at least one radio unit (e.g., remote radio unit (RRU), etc.), at least one antenna system (e.g., distributed antenna system (DAS), etc.), at least one radio network controller, and any other suitable components that constitute the RAN.

[0064] Network entity 120 is understood to include any other suitable equipment or devices involved in or related to the network system without departing from the scope of this disclosure. For example, network entity 120 may further include one or more equipment or devices constituting a data network (described below with reference to Figure 10), one or more equipment or devices related to a trusted third party (described below with reference to Figure 12), and so on.

[0065] Furthermore, the configuration illustrated in Figure 1 is only one possible embodiment, and the scope of this disclosure should not be limited thereto. Specifically, the system architecture may include one or more additional components, may include fewer components than those illustrated, and may be configured in a manner different from that illustrated.

[0066] For example, Figure 2 illustrates a block diagram of an example of a system configuration 200 for implementing an EMF according to one or more embodiments. The server node 210, EMF210-1, and network function 220-1 in Figure 2 may be the same as the server node 110, EMF110-1, and network function 120-1 in Figure 1, respectively.

[0067] As illustrated in Figure 2, the EMF210-1 and the network function 220-1 may be stored, deployed, and hosted on the same server node 210. For example, the server node 210 may include multiple storage media (e.g., servers, databases, etc.), and the EMF210-1 may be hosted in a first part of the server node 210, while the network function 220-1 may be hosted in a second part of the server node 210. According to the embodiment, the server node 210 may include one or more central servers or central nodes.

[0068] On the other hand, Figure 3 illustrates a block diagram of another example of a system configuration 300 for implementing EMF according to one or more embodiments. The first server node 310 and / or the second server node 320 in Figure 3 may be part of the server node 110 in Figure 1, and the EMF 310-1 and network function 320-1 in Figure 3 may be the same as the EMF 110-1 and network function 120-2 in Figure 1, respectively.

[0069] As illustrated in Figure 3, the EMF310-1 and network function 320-1 may be stored, deployed, and hosted on different server nodes. For example, the first server node 310 hosting the EMF310-1 may be located in a first geographical location, and the second server node 320 hosting the network function 320-1 may be located in a second geographical location, while the first geographical location may be different from the second geographical location. According to the embodiment, the first server node 310 may include one or more edge servers or edge nodes, and the second server node 320 may include one or more central servers or central nodes.

[0070] In view of the foregoing, the energy management function may be implemented efficiently and effectively in one or more communication systems. Thus, embodiments of the present disclosure may implement and utilize existing network infrastructure effectively and efficiently to manage the energy use of one or more network entities and enable optimization of energy efficiency with minimal cost, implementation effort, etc., and may be compatible with existing network infrastructure.

[0071] [Example of an implementation environment] As described above, the Energy Management Function (EMF) of the embodiment may be implemented on one or more server nodes. According to the embodiment, the server nodes may include cloud servers or cloud server clusters, and the EMF may be implemented in a cloud environment.

[0072] Figure 4 illustrates an example of an environment 400 in which the EMF, associated systems, and / or methods described herein may be implemented. As shown in Figure 4, the environment 400 may include multiple network entities 410, a server platform 420, and a network 430. The devices and components of the environment 400 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections.

[0073] Multiple network entities 410 may include one or more network entities (e.g., network functions, UEs, ANs, etc.) as described above with reference to Figures 1 to 3. For this reason, redundant descriptions related to them may be omitted below for simplicity.

[0074] The server platform 420 may include one or more servers capable of receiving, generating, storing, processing, and / or providing information. In some implementations, the server platform 420 may include a cloud server or a group of cloud servers. According to embodiments, the server platform 420 may include one or more server nodes as described herein. In some implementations, the server platform 420 may be designed to be modular so that certain software components may be swapped (in or out) depending on specific needs. Thus, the server platform 420 may be easily and / or quickly reconfigured for different applications or requirements.

[0075] In some implementations, as shown, the server platform 420 may be used in or comprise a cloud computing environment 422. While the implementations described herein describe the server platform 420 as being hosted in the cloud computing environment 422, in some implementations, the server platform 420 may not be cloud-based (i.e., it may be implemented outside a cloud computing environment) or may be partially cloud-based.

[0076] The cloud computing environment 422 includes an environment that hosts the server platform 420. The cloud computing environment 422 may provide services that do not require end-user knowledge of the physical location and configuration of the systems and / or devices that host the server platform 420, such as computation, software, data access, and storage. As shown, the cloud computing environment 422 may also include a group of computing resources 424 (collectively referred to as “computing resources 424” and individually as “computing resources 424”).

[0077] The computing resource 424 may include one or more personal computers, a cluster of computing devices, a workstation computer, a server device, or other types of computing and / or communication devices. In some implementations, the computing resource 424 may host a server platform 420. The cloud resource may include instances that compute and run on the computing resource 424, storage devices provided on the computing resource 424, and data transfer devices provided by the computing resource 424, etc. In some implementations, the computing resource 424 may communicate with other computing resources 424 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0078] As further shown in Figure 4, the computing resource 424 includes a group of cloud resources such as one or more applications ("APP") 424-1, one or more virtual machines ("VM") 424-2, virtualized storage ("VS") 424-3, and one or more hypervisors ("HYP") 424-4.

[0079] Application 424-1 may include one or more software applications that may be provided to or accessed by the network entity 410. Application 424-1 may eliminate the need to install and run software applications on the network entity 410. For example, Application 424-1 may include software associated with the server platform 420, software associated with the EMF, and / or any other software that can be provided via the cloud computing environment 422. In some implementations, one application 424-1 may send and receive information to and from one or more other applications 424-1 via a virtual machine 424-2.

[0080] The virtual machine 424-2 may include a software implementation of a device (e.g., a computer) that runs programs like a physical device. Depending on the extent to which the virtual machine 424-2 is used and its correspondence to any real-world device, the virtual machine 424-2 may be a system virtual machine or a process virtual machine. A system virtual machine may provide a complete system platform that supports the execution of a complete operating system ("OS"). A process virtual machine may run a single program or support a single process. In some implementations, the virtual machine 424-2 may run on behalf of a user (e.g., a user associated with one or more network entities 410) to manage the infrastructure and / or configuration of a cloud computing environment 422, such as data management, synchronization, or long-duration data transfer.

[0081] Virtualized storage 424-3 may include one or more storage systems and / or one or more devices or computing resources 424 that use virtualization technology within the storage systems. In some implementations, within the context of the storage system, the types of virtualization may include block virtualization and file virtualization. Block virtualization may represent an abstraction (or isolation) of logical storage from physical storage so that the storage system may be accessed without considering the physical storage or heterogeneous structure. Isolation can provide administrators of the storage system with flexibility in managing storage for end users. File virtualization may remove the dependency between data accessed at the file level and the location where the files are physically stored. This may enable optimized storage usage, server consolidation, and / or performance of non-destructive file migration.

[0082] The hypervisor 424-4 may provide hardware virtualization technology that enables multiple operating systems (e.g., "guest operating systems") to run simultaneously on a host computer such as computing resource 424. The hypervisor 424-4 may present a virtual operating platform to the guest operating systems and may manage the execution of the guest operating systems. Multiple instances of various operating systems may share virtualized hardware resources.

[0083] Network 430 may include one or more wired and / or wireless networks. For example, Network 430 may include cellular networks (e.g., 5G networks, 6G networks, LTE (long-term evolution) networks, 3G networks, CDMA (code division multiple access) networks, etc.), PLMN (public land mobile network), local area networks (LANs), wide area networks (WANs), MAN (metropolitan area networks), telephone networks (e.g., PSTN (Public Switched Telephone Network), private networks, ad hoc networks, intranets, the Internet, fiber optic networks, etc.), and / or combinations of these or other types of networks.

[0084] The number and arrangement of devices and networks shown in Figure 4 are provided as an example. In practice, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or devices and / or networks in different arrangements than those shown in Figure 4. Furthermore, two or more devices shown in Figure 4 may be implemented within a single device, and a single device shown in Figure 4 may be implemented as multiple distributed devices. In addition or alternatively, a set of devices in environment 400 (e.g., one or more devices) may perform one or more functions described as being performed by other sets of devices in environment 400.

[0085] In some embodiments, the Energy Management Function (EMF) of the embodiment described herein may be implemented or deployed on the aforementioned server platform 420 in the form of a virtualized network function (VNF). In this regard, the terms "virtual," "virtualized," etc., used herein are understood to be merely for the purpose of indicating the nature of a machine (and its associated elements and resources) provided in a virtual or software form. In this regard, the terms "virtual machine," "virtualized storage," etc., used herein should not be limited to a specific type of virtual machine or virtual element. Accordingly, it can be understood that the EMF may be defined or presented in the form of a containerized network function, with its functionality provided in the form of a container. A description of an example implementation configuration for implementing the EMF in the form of a containerized network function is provided below with reference to Figure 5.

[0086] To this end, by virtualizing and implementing the EMF on a server platform 420 separate from the network entity 410, energy management operations such as processing, calculating, and managing energy data can be centrally performed on a node separate from the network entity 410. As a result, energy consumption on the network entity 410 may be reduced, which can be particularly advantageous for network entities operating on an independent power supply (e.g., a battery).

[0087] Furthermore, resources for energy management (e.g., processing power, memory, storage, etc.) can be easily managed and dynamically scaled up or down according to demand, optimizing resource allocation and utilization. In addition, since energy data and information are managed collectively by EMF, energy data and information can be easily and securely managed, and said energy data and information can be easily replicated or backed up to provide redundancy, so that access to said energy data and information may be authorized and authenticated only for trusted entities.

[0088] [Example of implementing containerized energy management functionality] As described above, the energy management function (EMF) according to one or more embodiments may be implemented in the form of a containerized network function. Below, a description of an example configuration for implementing a containerized energy management function is provided.

[0089] Figure 5 illustrates a block diagram of an example of the components of a server node 500 according to one or more embodiments. The server node 500 may correspond to any of the server nodes in Figures 1 to 3, and may be configured to implement the server platform in Figure 4.

[0090] In this embodiment, the Energy Management Function (EMF) may be defined in software form, for example, through containerization (or any other suitable technique). Thus, the containerized EMF may be deployed in container form on the server node 500, and the functions of the Energy Management Function may be executed or implemented through the execution or orchestration of containers associated with the Energy Management Function.

[0091] As illustrated in Figure 5, the server node 500 may include multiple containers 511-512 and 521-522. The containerized EMF may be subdivided or distributed among the multiple containers 511-512 and / or 521-522. For example, the functionality of the EMF may be separated into multiple parts (e.g., a first part of the functionality relates to a first operation, a second part of the functionality relates to a second operation, etc.), and the multiple parts of the functionality may be distributed among containers 511-512 and / or containers 521-522. In addition or alternatively, the EMF may be separated in a similar manner according to the type of network functionality associated with it (e.g., AMF, SMF, NWDAF, NRF, NEF, etc.).

[0092] According to one embodiment, the server node 500 may include a Kubernetes (K8s) node, and the EMF containers may be grouped or aggregated in their respective pods (for example, containers related to the first function of EMF may be included in the first pod 510, and containers related to the second function of EMF may be included in the second pod 520, etc.).

[0093] Multiple pods on server node 500 may share the same resources (e.g., CPU, memory, etc.) provided by server node 500. Resources allocated to the EMF may be managed by coordinating the pods and / or containers associated with the EMF. For example, resources may be scaled up by increasing the number of associated containers and / or pods, or scaled down by decreasing the number of associated containers and / or pods.

[0094] The configuration illustrated in Figure 5 is simplified for descriptive purposes and should not be understood as limiting the scope of this disclosure. Specifically, in practice, the server node 500 may include any suitable components for hosting and running multiple pods, and without departing from the scope of this disclosure, the number of pods may be more than two, and each pod may contain more than two containers. Furthermore, the containerized EMF may be understood as being hosted or deployed on multiple server nodes in a similar manner as described above. Furthermore, the multiple nodes may be understood as containing the same container (or pod) to provide redundancy and enhance network availability.

[0095] In view of the foregoing, embodiments of this disclosure may take advantage of the benefits of containerization when implementing EMF for energy management provisioning. For example, implementing a containerized EMF may allow the EMF to scale efficiently on demand, be easily replicated and coordinated across server nodes, and provide improved scalability to enable efficient resource utilization and seamless scaling.

[0096] Furthermore, containerized EMFs can be rapidly instantiated, migrated, and updated, enabling faster time to market for new high-energy-efficiency and / or energy management services and features. Additionally, EMF functionality can be managed by coordinating the associated containers, enabling independent development, testing, and deployment of the EMF.

[0097] In addition, implementing a containerized EMF may improve resource utilization efficiency, leverage container-specific security features to enhance system security, provide improved portability and interoperability, and enable seamless integration with different systems or platforms.

[0098] [Example of server node components] As described above, an energy management function (EMF) according to one or more embodiments may be implemented in one or more server nodes. Below, examples of server node components for implementing EMF and examples of their associated configurations are provided.

[0099] Figure 6 illustrates a block diagram of an example of the components of a server node 600 according to one or more embodiments. The server node 600 may correspond to any of the server nodes described above with reference to Figures 1 to 5.

[0100] As illustrated in Figure 6, the server node 600 may include at least one communication interface 610, at least one storage 620, and at least one processor 630, but it can be understood that the server node 600 may include more or fewer components than those illustrated in Figure 6, and / or may be arranged in a different manner than those illustrated in Figure 6, without departing from the scope of this disclosure. For example, as described below with reference to Figure 7, the server node of the embodiment may include one or more additional components such as input / output modules. The components of one or more server nodes 600 may be implemented using hardware, software, firmware, or any combination thereof.

[0101] The communication interface 610 may include at least one transceiver-like component (e.g., transceivers, other receivers and transmitters, buses, interconnects, etc.) that enables the components of the server node 600 to communicate with each other and / or with one or more components outside the server node 600 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0102] For example, the communication interface 610 may connect the processor 630 to the storage 620, allowing them to communicate and interact with each other when performing one or more operations. As another example, the communication interface 610 may connect a server node 600 (or one or more components contained therein) to one or more network entities, allowing them to communicate and interact with each other. Furthermore, the communication interface 610 may include, for example, an ATA (Advanced Technology Attachment) adapter, a Serial ATA (SATA) adapter, a SCSI (Small Computer System Interface) adapter, a RAID (redundant array of inexpensive disks) controller, a Storage Area Network (SAN) adapter, a network adapter, and / or any other suitable components.

[0103] In some embodiments, the communication interface 610 may include a component or mechanism configured to communicate with multiple network entities (and / or one or more associated OAM tools) in order to obtain one or more energy data of one or more network entities. In some implementations, the communication interface 610 may include at least one service-based interface (SBI) that enables the EMF to communicate with one or more network functions (e.g., one or more network functions 120-1).

[0104] For example, interaction and communication between the EMF and one or more network functions may be performed via a dedicated SBI interface, which is referred to here as "Nemf". The energy management functions of the EMF may be exposed to network entities via the Nemf interface. In practice, the labeling of the EMF's SBI interface may be presented in any appropriate term such as "Nnesf" or "Nesf" without departing from the scope of this disclosure.

[0105] According to one embodiment, the communication interface 610 may include a plurality of interfaces defined by a reference point representation. For example, the communication interface 610 may include at least three new interfaces (N110, N111, N112). A further description of these interfaces is provided below with reference to Figure 13.

[0106] In some embodiments, the communication interface 610 may include one or more application programming interfaces (APIs) that enable the server node 600 (or one or more components contained therein) to communicate with one or more software applications (e.g., software applications deployed in network entities, virtualized network functions, etc.). In some implementations, the APIs may interact with multiple network functions exposed through the Nemf SBI and / or SBIs associated with their respective network functions.

[0107] The storage 620 may include one or more storage media suitable for storing data, information, and / or computer-executable instructions. According to embodiments, the storage 620 may include at least one memory storage such as random access memory (RAM), read-only memory (ROM), programmable ROM (PROM), and / or other types of dynamic or static storage devices (e.g., flash memory, magnetic memory, and / or optical memory) for storing information and / or computer-readable instructions for use by the processor 630. A description of an example of memory storage is provided below with reference to the memory 720 in Figure 7.

[0108] In addition or alternatively, storage 620 may include hard disks (e.g., magnetic disks, optical disks, magneto-optical disks, and / or solid-state disks), compact discs (CDs), digital multipurpose discs (DVDs), floppy disks, cartridges, magnetic tapes, and / or other types of non-temporary computer-readable media, accompanied by corresponding drives.

[0109] According to some embodiments, the storage 620 may include at least one database containing multiple storage media, such as hard disks and / or solid-state disks in a RAID configuration. In some embodiments, the database may include a SAN and / or NAS (network attached storage) system. According to some embodiments, the database may correspond to a distributed storage system, where each database is configured to store custom information such as historical data on the energy efficiency level of each network entity, predicted energy usage patterns of each network entity, energy optimization rules or policies related to different network entities, the level of energy efficiency achieved, and the types of network resources / parameters related to each network function. A description of an example database is provided below with reference to database 730 in Figure 7.

[0110] According to the embodiment, the storage 620 may be configured to store information such as raw data and metadata obtained from one or more network entities (and / or one or more OAM tools associated therewith). In addition or alternatively, the storage 620 may be configured to store one or more pieces of information related to one or more operations performed by the processor 630. For example, the storage 620 may store one or more energy data received from one or more network entities (and / or one or more OAM tools associated with one or more network entities), one or more energy calculation results calculated or generated by at least one processor 630, information about network entities involved in operations performed by the processor 630, information about the operation history performed by the processor 630, information necessary to perform the operations (e.g., energy management policy), etc.

[0111] Furthermore, storage 620 may be configured to store or host the EMF and one or more pieces of information associated therewith (e.g., computer-readable instructions for implementing the EMF, resources required to run the EMF, programming code for the EMF, policies or predetermined thresholds related to energy management, etc.). According to some embodiments, storage 620 may be configured to store or host one or more network functions. For example, storage 620 may store or host one or more network functions described herein, such as AMF, SMF, NWDAF, UPF, NRF, NEF, etc.

[0112] In some implementations, storage 620 may include multiple storage media, and storage 620 may be configured to store duplicates or copies of at least some of the information in the multiple storage media in order to provide redundancy and back up the information or related data.

[0113] The processor 630 may include at least one processor that can be programmed or configured to perform the functions or operations described herein. According to one embodiment, the processor 630 may be configured to receive one or more signals and / or instructions to trigger one or more operations (for example, via a communication interface 610, etc.).

[0114] Furthermore, the processor 630 may be implemented in hardware, firmware, or a combination of hardware and software. For example, the processor 630 may include at least one general-purpose or dedicated processing unit, such as a central processing unit (CPU), graphics processing unit (GPU), general-purpose GPU (GPGPU), acceleration unit (APU), microprocessor, microcontroller, digital signal processor (DSP), field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), integrated system (bus) controller, memory management control unit, floating-point unit, hardware accelerator, dedicated computer chip, and / or at least one of other types of processing or arithmetic units. According to embodiments, the processor 630 may include a single-core processor, a multi-core processor, or a combination of one or more single-core processors and / or one or more multi-core processors.

[0115] The processor 630 may include a plurality of arithmetic units or processing units, some of which may be associated with one or more dedicated processes or operations. For example, as further described below with reference to Figure 7, the processor may include at least one energy arithmetic module associated with operations for calculating energy data, and at least one energy management module associated with operations for managing energy efficiency.

[0116] In some embodiments, the processor 630 may be configured to execute an EMF stored in at least one storage medium or memory storage (e.g., storage 620, etc.) and perform one or more actions or one or more operations described herein. In addition or alternatively, the processor 630 may be configured to execute computer-readable instructions related to the EMF and perform one or more actions. For example, the processor 630 may execute an EMF (or related instructions) to request, collect, and / or retrieve one or more energy data of one or more network entities (e.g., those described above with reference to Figures 1 to 5), to process the retrieved energy data, or to perform one or more operations to facilitate the provisioning of energy management to optimize the energy efficiency of one or more network entities. In addition, the processor 630 may be configured to execute an EMF (or related instructions) to interact with one or more network functions (e.g., one or more network functions of the core network of a network system as described above). A description of examples of operations that may be performed by the processor 630 is provided below with reference to Figures 8 to 12.

[0117] Figure 7 illustrates an example of the configuration of components of a server node 700 according to one or more embodiments. One or more components of server node 700 may also be some of the components of server node 600 in Figure 6. For example, the communication interface 710 and processor 740 in server node 700 may be the same as the communication interface 610 and processor 630 in server node 600, respectively. Furthermore, the memory 720 and database 730 in server node 700 may also be some of the storage 620 in server node 600. Thus, the features of server node 600 and server node 700 described herein may be mutually applicable unless otherwise specified. Furthermore, any related redundant descriptions may be omitted below for simplification.

[0118] As illustrated in Figure 7, components in the server node 700 may be coupled to each other in a communicative or operable manner and may be configured to interact with each other. Generally, the processor 740 (or associated modules) may be configured to execute instructions 721 stored in memory 720 and / or to utilize energy management policies 731 stored in database 730 to perform one or more operations related to energy management. In some implementations, the instructions 721 may be related to a first part of the EMF, and the energy management policies 731 may be related to a second part of the EMF.

[0119] The energy calculation module 741 of the processor 740 may execute instruction 721 to communicate with multiple network entities (e.g., network entity 120, etc.) and receive energy data from multiple network entities (and / or one or more OAM tools associated with multiple network entities) via the communication interface 710. In this way, the energy calculation module 741 may execute instruction 721 to process the received energy data. Subsequently, the energy management module 742 of the processor 740 may utilize one or more energy management policies 731 (stored in the database 730) and the processed energy data to perform one or more energy management operations.

[0120] One or more policies 731 may include, for example, policies and quality of service (QoS) requirements set by a network operator or service provider. One or more policies may be used by a server node (or at least one associated processor) to determine whether the energy efficiency level of a network entity is within acceptable / unacceptable levels. For example, one or more policies 731 may include a set of predetermined rules or thresholds that define the minimum energy efficiency required to ensure promised QoS, maintain carbon emissions within predetermined levels, ensure a percentage of renewable energy use as an energy resource, etc.

[0121] In some embodiments, one or more policies 731 may specify network resources / parameters of a network entity, which may be updated based on the energy efficiency level determined for that network entity. For example, a predetermined rule in one or more policies 731 may indicate rejection of connection requests received by the NSACF, such as blocking connections when connection ≥ 50 and latency ≥ 100 ms. In another example, a predetermined rule in one or more policies 731 may stipulate that connections should be allowed for specific services when only certain services are supported by a network system with connection-resource constraints. Note that the aforementioned one or more policies 731 and their associated predetermined rules are provided for illustrative purposes only, and one or more policies 731 may have multiple predetermined rules with different constraints on network resources / parameters to optimize energy consumption and support energy efficiency in the communication system.

[0122] Furthermore, information such as instructions for performing actions or operations, and updates to policies may be received from one or more users (e.g., network operators, end users, etc.) via the input / output module 750. Additionally, information such as data calculations and the results of performed operations may be output to one or more users via the input / output module 750.

[0123] The input / output module 750 may include one or more components or mechanisms configured to receive data or information and / or provide output data or information. According to embodiments, the input / output module 750 may include at least one input interface (e.g., a touchscreen display, buttons, switches, microphones, sensors, keyboards, mice, joysticks, keypads, soft keys, etc.) and / or at least one output interface (e.g., a display, speaker, ringer, one or more light-emitting diodes (LEDs), LED-based displays such as active-matrix organic light-emitting diode (AMOLED) displays, thin-film transistor (TFT) displays, liquid crystal displays (LCDs), etc.).

[0124] According to the embodiment, the processor 740 (or a module contained therein) may execute instructions 721 to (1) receive data relating to the energy consumption of one or more network entities over a predetermined period of time (e.g., from one or more network entities and / or one or more associated OAM tools, etc.), (2) manage the energy consumption level of at least one network entity based on one or more energy management policies 731, (3) determine the energy efficiency level of each network entity based on the corresponding energy consumption, (4) determine the total energy efficiency of the network system based on the energy efficiency level associated with each network entity of the multiple network entities, (5) identify one or more network resources / parameters for energy optimization in at least one network entity of the multiple network entities, (6) receive the energy usage pattern of at least one network entity of the multiple network entities based on the current energy consumption of one or more network entities, and / or (7) dynamically adapt one or more network resources for at least one network entity based on the energy optimization policy. According to one embodiment, the processor 740 (or a module contained therein) may be configured to execute instructions 721 to (1) provide information regarding the energy efficiency level of each network entity to one or more user devices associated with one or more users, and / or (2) provide the total energy efficiency of the communication network to one or more users.

[0125] For this purpose, embodiments of the present disclosure may provide one or more server nodes on which the EMF may be implemented and deployed. For this purpose, one or more server nodes (or one or more processors associated therewith) may be configured to execute the EMF (or instructions for implementing the EMF) to perform one or more operations for provisioning energy management in a communication system. A description of some examples of operations that may be performed by the server nodes of the present disclosure is provided below with reference to Figures 8–12.

[0126] [Examples of operations and use cases] As previously stated, embodiments of the present disclosure provide a server node (or any other suitable device) which may utilize or execute an Energy Management Function (EMF) (or instructions for implementing an EMF) to perform one or more energy management operations. Descriptions of examples of operations that can be performed by the server node (or any other suitable device) of the embodiments, and descriptions of related use cases, are provided below with reference to Figures 8 to 12.

[0127] Figure 8 illustrates a flowchart of an example of a method 800 for provisioning energy management according to one or more embodiments. One or more operations of method 800 may be performed by the apparatus of the embodiment. Specifically, one or more operations may be performed by one or more server nodes, and one or more server nodes may include at least one processor (e.g., processor 630, processor 740, etc.) which may be configured to perform one or more operations described herein when executing EMFs (or instructions for implementing EMFs) stored in one or more storage media (e.g., storage 620, memory 720, database 730, etc.).

[0128] As illustrated in Figure 8, in operation S810, the server node may be configured to receive one or more energy data. Specifically, the server node may communicate with multiple network entities (e.g., network entity 120) via one or more communication interfaces (e.g., communication interface 610, communication interface 710, etc.) to receive one or more energy data from there. According to the embodiment, one or more measurements (e.g., energy measurement, performance measurement, etc.) of multiple network entities may be performed by one or more OAM tools, and the EMF may subscribe to one or more OAM tools. In this case, in operation S810, the server node may request one or more energy data from one or more OAM tools, and one or more OAM tools may provide the requested one or more energy data accordingly.

[0129] For example, when a server node executes an EMF (or related instruction), it may generate one or more requests or queries and provide these requests / queries to one or more network functions (or one or more components deploying such one or more network functions) via at least one SBI (e.g., Nemf). One or more requests / queries may be provided to one or more network functions via one or more APIs. Subsequently, one or more network functions may provide the requested energy data to the server node in a similar manner.

[0130] According to one embodiment, a server node may be configured to continuously (or periodically) request and receive energy data in real time or near real time. Thus, the energy data may be used for real-time or near real-time energy management to dynamically manage the energy of network entities according to real-time or near real-time conditions or requirements.

[0131] According to the embodiments, the energy data described herein may include, but is not limited to, the following: • Energy consumption information: This information may include energy consumption levels of one or more network entities, such as energy consumed in one or more operations of one or more network functions, energy consumed in one or more operations of one or more network services, energy consumed in one or more operations of one or more network slices, energy consumed in one or more protocol data unit (PDU) sessions of the UE, energy consumed by one or more operations of the UE, and energy consumed by components of the AN (e.g., base stations). Furthermore, this information may include historical data related to the energy consumption of each network entity. • Energy Profile: This information may show how energy consumption changes under different conditions, such as idle mode, low traffic, peak traffic, specific configuration, and specific duration. Furthermore, this information may include predictions of energy usage patterns. • Energy metrics: This information may provide quantitative performance indicators regarding the energy efficiency of one or more network entities, and may include metrics such as energy per bit, energy per user, energy per operation, and energy per service. This information may include historical and / or predicted energy metrics. • Network information: This information may include network configuration and network topology, such as the number and placement of base stations, cell types (e.g., small cells, femtocells, etc.), equipment types (e.g., high energy-efficient hardware, optimized software, etc.), and energy resource information (e.g., renewable, non-renewable, etc.). • Component status: This information may include the status of hardware components (e.g., base station health, resource availability status of servers hosting network functions, etc.) and the status of software components (e.g., version number, etc.).

[0132] The energy data described herein may be understood to include any appropriate data or information that may be used to determine the energy efficiency of a network entity, in addition to or instead of the examples provided above. For example, as described below with reference to Use Case Examples 1 to 4, the energy data may further include forecast data and / or information on one or more energy efficiency factors.

[0133] In view of the foregoing, in Operation S810, the server node may acquire or receive data or information that enables the server node to facilitate the provisioning of energy management for one or more network entities when it is being analyzed or processed.

[0134] Still referring to Figure 8, when performing operation S810, method 800 may proceed to operation S820, in which the server node may be configured to execute an EMF (or related instruction) to process energy data.

[0135] According to the embodiment, a server node may determine energy consumption information for one or more network entities based on energy data. For example, the energy data may include energy metrics over a period of time related to the energy metrics, and the server node may determine the energy consumption of one or more network entities based on the energy metrics and the period. The server node may be configured to determine the total energy consumption of a particular network entity over a specific period, the total energy consumption of a particular group of network entities over a specific period, the partial energy consumption of a particular network entity over a specific period, the partial energy consumption of a particular group of network entities over a specific period, the total / partial energy consumption of a particular operation, the total / partial energy consumption of a particular group of operations, and so on.

[0136] According to one embodiment, the energy data may include energy consumption information and energy metrics (e.g., performance indicators) of at least one of a plurality of network entities, and the server node may determine the energy efficiency level of at least one network entity based on the energy consumption information and energy metrics.

[0137] According to one embodiment, the energy data may include energy consumption information and energy metrics for multiple network entities, and the server node may determine the energy efficiency level of each of the multiple network entities based on the energy consumption information and energy metrics.

[0138] According to one embodiment, a server node may determine the total / partial energy efficiency of at least a portion of the network system. For example, the server node may determine the total energy efficiency of the entire network system based on the energy efficiency level associated with each of at least a number of network entities. As another example, the server node may determine the partial energy efficiency of a portion of the network system based on the energy efficiency level associated with at least a number of network entities.

[0139] Still referring to Figure 8, when processing energy data in operation S820, method 800 may proceed to operation S830, in which the server node may be configured to execute an EMF (or related instructions) to perform one or more operations for provisioning energy management (which may be referred to here as “energy management operations”) for the relevant network entity. Alternatively or in addition, when performing operation S820, method 800 may return to operation S810, in which the server node may be configured to receive further energy data.

[0140] According to the embodiment, one or more energy management operations may include one or more operations for managing energy information. For example, a server node may report, publish, or expose information on energy consumption and / or energy efficiency levels to one or more network entities and / or one or more users. For example, the server node may provide the information to one or more network functions (via a communication interface) with or without instructions to use the information, so that one or more network functions may use the information for energy management.

[0141] As another example, a server node may share the aforementioned information with one or more relevant trusted third parties (e.g., vendors, service providers, site management companies, authorized users, etc.). As yet another example, a server node may continuously or periodically store, back up, update, and / or remove energy information on one or more storage media (e.g., servers, etc.). One or more of the above operations may be performed continuously, periodically, or over a specific period of time.

[0142] In some embodiments, one or more energy management operations may include one or more operations for managing at least one target network entity. For example, a server node may identify at least one network entity with low priority or low severity in the network system from a group of network entities based on energy efficiency levels related to multiple network entities, where at least one target network entity may include at least one network entity that has an energy efficiency level that violates at least one predetermined threshold (e.g., a network entity with a low energy efficiency level, a network entity with a high energy efficiency level but that consumes a large amount of resources, etc.). At least one predetermined threshold may be related to at least one quality of service (QoS) requirement, which may be defined in at least one energy management policy (e.g., component 731 in Figure 7, etc.).

[0143] When determining at least one target network entity, the server node may perform one or more operations to manage the at least one target network entity. Specifically, the server node may determine the cause or factor that resulted in the energy efficiency level of the at least one target network entity (e.g., low energy efficiency, capped energy efficiency, etc.), and may determine one or more operations to manage the at least one target network entity from an action playbook containing a list of operations. The one or more operations may include resource management, operation management, state management, energy standard management, etc.

[0144] For example, based on the determination that at least one target network entity has low energy efficiency due to a partial failure of hardware resources, the server node may allocate additional hardware resources to the target network entity or redeploy the network entity to healthy hardware, etc. Furthermore, based on the determination that at least one target network entity has capped energy efficiency (e.g., the energy efficiency level has reached its maximum level and / or has not increased over a period of time), the server node may allocate additional resources to the target network entity, for example, to further improve the energy level or reduce redundant resources. Furthermore, based on the determination that one or more renewable energy resources are available, the server node may allocate at least a portion of the energy resources associated with at least one target network entity to one or more renewable energy resources.

[0145] As another example, based on the determination that at least one target network entity has low energy efficiency due to one or more operations (e.g., an excessive amount of parallel operations, an operation that consumes a large amount of energy, etc.), the server node may, for example, instruct at least one target network entity to interrupt or terminate operations that have a low priority or are not essential / of low importance to the network system, or it may generate and provide at least one target network entity with a schedule for performing operations sequentially in an optimized manner, or it may assign operations to other network entities.

[0146] As yet another example, based on the determination that at least one target network entity has low energy efficiency and / or is reducing the energy efficiency of other network entities, the server node may set the state of at least one target network entity to idle, sleep, or off.

[0147] As yet another example, a server node may manage one or more energy criteria related to at least one target network entity based on the energy efficiency level of at least one target network entity. For example, a server node may fine-tune, update, adjust, prioritize, add, remove, duplicate, etc., one or more energy criteria related to at least one target network entity. In this regard, the term “energy criteria” as used herein may refer to configurations or mechanisms related to energy efficiency, such as power saving mechanisms (e.g., configurations for dynamic spectrum sharing, power level adjustment schemes, etc.), network configurations (e.g., network topology, network entity deployment strategies, etc.), and device configurations (e.g., antenna configurations, radio transmission parameters, permissible operations in idle state, conditions for entering sleep mode, etc.).

[0148] In view of the above, the server node may automatically and appropriately receive one or more energy data from one or more network entities (and / or one or more associated OAM tools), process and manage the received energy data, perform one or more energy management operations on one or more network entities, and execute EMF (or related instructions) to optimize the energy efficiency of one or more network entities. The following describes some example use cases in which the operations described herein may be implemented.

[0149] [Use Case Example 1: Predictive Energy Management] According to one embodiment, a server node may be configured to execute an EMF (or related instructions) to interact with one or more network functions in energy management provisioning. Below is a description of one use case in which the EMF interacts with a Network Data Analysis Function (NWDAF) when providing predictive energy management.

[0150] Figure 9 illustrates a block diagram of an example of a system configuration 900 related to a first use case according to one or more embodiments. As illustrated in Figure 9, the system configuration 900 may include an EMF 910 (or a device that deploys the EMF 910, such as a server node in the embodiment), a plurality of network entities 920, and an NWDAF 930 (or a device that deploys the NWDAF 930). The EMF 910 may be the same as the EMF described herein. The NWDAF 930 may be one of the plurality of network functions described herein, and the network entities 920 may include the remaining network functions, UE, AN, etc. described herein.

[0151] The EMF910, multiple network entities 920, and NWDAF930 may be coupled to each other in a communicative and operational manner via one or more appropriate communication interfaces such as SBIs as described herein. For example, the EMF910 may communicate with network entity 920 via the Nemf interface, network entity 920 may communicate with NWDAF930 via the Nnwdaf interface, and the EMF910 may communicate with NWDAF930 via the Nemf interface and / or the Nnwdaf interface.

[0152] In practice, the EMF910, the multiple network entities 920, and the NWDAF930 may be hosted or deployed in one or more devices, equipment, or apparatus, such as one or more server nodes described herein. Thus, the communication and interoperation between the EMF910, the multiple network entities 920, and the NWDAF930 may be understood to be presented or defined in relation to the communication and interoperation between the related devices, equipment, or apparatus. Similarly, the one or more operations that can be performed by the EMF910 and NWDAF930 described herein may be performed by the devices, equipment, or apparatus on which the EMF910 and NWDAF930 are hosted or deployed.

[0153] In this regard, the NWDAF930 described herein may represent a component within a 3GPP system architecture (e.g., a 5G system, a 6G system, etc.) responsible for performing data analysis tasks. In the context of energy management, the NWDAF930 may be used to collect energy data, process the energy data to obtain meaningful information and insights, and provide support for various network functions and the network services based thereon.

[0154] For example, in the example in Figure 9, NWDAF930 may communicate with one or more network entities 920 to continuously (or periodically) request and receive energy data. Alternatively, NWDAF930 may subscribe to one or more OAM tools to continuously (or periodically) request and receive energy data. In this regard, the energy data may include raw data (e.g., raw data, metadata, etc.), such as those described above with reference to operation S810 in Figure 8. Additionally, NWDAF930 may communicate with EMF910 and receive energy data from it. For example, a server node may be configured to execute EMF910 (or related instructions) to send a prediction request to NWDAF930 to predict the energy usage pattern of at least one of the network entities 920. The prediction request may include processed and / or unprocessed energy data (e.g., obtained by the EMF910 via multiple network entities 920 and / or associated OAM tools), such as the current energy consumption of at least one network entity of one or more network entities 920, and data used to determine the current energy consumption.

[0155] When receiving energy data from EMF910 and / or network entity 920, NWDAF930 may perform one or more operations to process the energy data. According to embodiments, the one or more operations may include data mining, machine learning, statistical analysis, and / or any other appropriate operations that may identify patterns, relationships, correlations, trends, etc., in the energy data. Thus, based on the analyzed data, NWDAF930 may generate insights (e.g., key energy parameters related to energy efficiency, anomalous operations that may result in low levels of energy efficiency), recommendations (e.g., possible adjustments to one or more configurations on network entities to improve energy efficiency), and predictions (e.g., future energy use / efficiency patterns, the impact of low / high energy efficiency, network traffic predictions, etc.).

[0156] Next, NWDAF930 may provide EMF910 with data or information such as the insights, recommendations, and forecasts (which may be referred to as “forecast data”) described herein. In this regard, in operation S810 of method 800 (described above with reference to Figure 8), it may be understood that the forecast data may be received by the server node (which is deploying or running EMF910) in the form of the described energy data, or in addition to the described energy data. For example, in operation S810, when the server node requests energy data from other network entities, it may request and receive forecast data from NWDAF930 in a similar manner as described above. Alternatively or in addition, the server node may request and receive forecast data from NWDAF930 after processing energy data (operation S820) and / or after performing one or more energy management operations (operation S830).

[0157] Thus, the server node may use the forecast data along with the energy data to perform one or more forecast energy management operations. For example, the server node may provide the NWDAF930 with information on the energy consumption of at least one network entity and request the NWDAF930 to perform a forecast for the future energy usage patterns of at least one network entity. The NWDAF930 may process the received information, generate the requested forecast, and provide the generated forecast to the server node. Subsequently, the server node may execute an EMF (or related instruction) to process the energy data (received in operation S810) related to one or more network entities, taking into account the forecast for future energy usage patterns.

[0158] For this purpose, the server node of the embodiment may utilize the EMF910 while leveraging the data analysis capabilities of the NWDAF930 for performing predictive energy management. In this way, the network entity 920 and its associated resources and operations may be dynamically and effectively coordinated for optimal energy efficiency.

[0159] It can be understood that one or more operations related to the NWDAF930 may be implemented in conjunction with one or more operations of the other use cases described herein, so that predictive energy management may be performed in those other use cases.

[0160] [Use Case Example 2: Energy Management in Access, Mobility, and Session Management Operations] As described above, according to the embodiment, a server node may be configured to utilize EMF to interact with one or more network functions in provisioning energy management. Below is a description of a use case in which EMF interacts with access and mobility management functions (AMF), session management functions (SMF), and user plane functions (UPF) when providing energy management.

[0161] Figure 10 illustrates a block diagram of an example of a system configuration 1000 related to a second use case according to one or more embodiments. As illustrated in Figure 10, the system configuration 1000 may include EMF1011-1, AMF1011-2, SMF1011-3, UPF1012-1, user equipment (UE)1020-1, access network (AN)1020-2, and data network (DN)1020-3. EMF1011-1 may be the same as the EMF described herein, and AMF1011-2, SMF1011-3, UPF1012-1, UE1020-1, AN1020-2, and DN1020-3 may be part of the network entities described herein.

[0162] According to the embodiment, EMF1011-1, AMF1011-2, and SMF1011-3 may constitute part of the control plane 1011, and UPF1012-1 may constitute part of the user plane 1012. Alternatively or in addition, part of EMF1011-1 may be associated with the user plane 1012.

[0163] In Figure 10, EMF1011-1 and other components may be coupled to each other in a communicative and operational manner via appropriate communication interfaces. For example, EMF1011-1 may communicate with AMF1011-2 via the Nemf interface and / or Namf interface; EMF1011-1 may communicate with SMF1011-3 via the Nemf interface and / or Nsmf interface; AMF1011-2 may communicate with UE1020-1 via the N1 interface and with AN1020-2 via the N2 interface; SMF1011-3 may communicate with UPF1012-1 via the N4 interface; AN1020-2 may communicate with UPF1012-1 via the N3 interface; and UPF1012-1 may communicate with DN1020-3 via the N6 interface. In practice, EMF1011-1 and at least some of the network entities 1011-2 to 1020-3 may be hosted or deployed on one or more devices, equipment, or apparatus (such as one or more server nodes described herein). Thus, communication and interoperation between EMF1011-1 and the network entities 1011-2 to 1020-3 may be presented or defined in relation to communication and interoperation between the relevant devices, equipment, or apparatus. Similarly, one or more operations that can be performed by EMF1011-1, AMF1011-2, SMF1011-3, and UPF1012-1 described herein may be performed by the devices, equipment, or apparatus on which EMF1011-1, AMF1011-2, SMF1011-3, and UPF1012-1 are hosted or deployed.

[0164] Furthermore, while Figure 10 illustrates that server node 1010 includes EMF1011-1, AMF1011-2, SMF1011-3, and UPF1012-1, it can be understood that EMF1011-1, AMF1011-2, SMF1011-3, and / or UPF1012-1 may be hosted or stored on different server nodes without departing from the scope of this disclosure. For example, EMF1011-1 may be deployed or hosted on a first server node (e.g., one or more edge server nodes), and AMF1011-2, SMF1011-3, and UPF1012-1 may be deployed or hosted on a second server node (e.g., one or more central server nodes).

[0165] The AMF1011-2 described herein may represent an entity responsible for managing the access and mobility operations of network entities and ensuring efficient and secure connectivity between network entities. For example, when UE1020-1 first accesses the network system, access procedures (e.g., authorization, resource allocation, etc.) may be performed by AMF1011-2 to enable UE1020-1 to communicate securely and efficiently with other network entities such as AN1020-2. AN1020-2 may include a radio access network (RAN), which may include at least one base station (e.g., eNodeB, gNodeB, etc.), at least one radio unit (e.g., remote radio unit (RRU), etc.), at least one antenna system (e.g., distributed antenna system (DAS), etc.), at least one radio network controller, and any other suitable components.

[0166] In light of the above, the AMF1011-22 plays a crucial role in the network system, as it is responsible for managing access to the network by numerous network entities and handling mobility-related functions. Therefore, it is important to provide optimal energy management for the AMF1011-2 to ensure its energy efficiency. In this regard, some examples of factors that may affect the energy efficiency of the AMF1011-2 include the following: • Network Traffic Load: The amount of network traffic handled by the AMF1011-2 can affect the energy efficiency of the AMF1011-2. Generally, higher traffic loads require more processing power and resources, leading to increased energy consumption and potentially impacting the energy efficiency of the AMF1011-2. • Network Topology: The network topology, including the number and distribution of network nodes / entities hosting the AMF1011-2, can affect the energy efficiency of the AMF1011-2. For example, the network topology can affect the signaling scheme of the AMF1011-2 and the number of processes and operations (e.g., handovers) performed by the AMF1011-2. • Resource Management: Resource management, such as scheduling and allocation of wireless and network resources, can affect the energy efficiency of the AMF1011-2. • Operating Modes: Available operating modes and associated configurations can affect the energy efficiency of the AMF1011-2. For example, an AMF in sleep mode or low power mode, implemented during periods of inactivity, can reduce energy consumption and improve the energy efficiency of the AMF1011-2. Furthermore, the configuration of sleep mode or low power mode, such as the number of operations allowed in active cycles, inactive cycles, and low power mode, can also affect the energy efficiency of the AMF1011-2. • Routing and handover algorithms: The routing and handover algorithms used by the AMF1011-2 can affect the number of unnecessary handovers, signaling overhead, and energy waste, potentially impacting the energy consumption and energy efficiency of the AMF1011-2. • Processing and computational load: The computational load on the AMF1011-2, such as the type of signaling and control functions, can affect energy efficiency. For example, processing or calculating complex signaling will consume more energy, which can affect the energy consumption and energy efficiency of the AMF1011-2. • Network protocol configuration: The design of the network protocol used by the AMF1011-2 may affect the energy efficiency of the AMF1011-2. For example, the protocol design, such as the protocol message format, may affect the number of control messages that need to be sent during operation, and thus affect the energy consumption and energy efficiency of the AMF1011-2.

[0167] Factors that may directly and / or indirectly affect energy efficiency (which may be referred to herein as “energy efficiency factors”) may, without departing from the scope of this disclosure, further include any other suitable energy efficiency factors.

[0168] According to one embodiment, a server node may execute EMF1011-1 (or related instructions) to perform one or more operations of method 800 in order to provide energy management to AMF1011-2. For example, when using EMF10111-1, the server node may communicate with AMF1011-2 in a similar manner to those described above with reference to operation S810 (via the Nemf interface and / or Namf interface) to acquire and receive energy data.

[0169] In this regard, the received energy data may be understood to include, in addition to or instead of, the examples of energy data described above with reference to Figure 8, one or more of the aforementioned energy efficiency factors. Furthermore, the server node may communicate with the NWDAF (or one or more components hosting the NWDAF) to obtain predicted energy data related to the AMF1011-2 from there.

[0170] When receiving energy data (whether or not prediction data is available), the server node may process the received energy data in a similar manner to those described above, with reference to operation S820. According to one embodiment, the server node may determine one or more optimal configurations for the AMF1011-2 based on the received energy data and one or more energy management policies. For example, the server node may determine the energy efficiency level of the AMF1011-2 and whether the energy efficiency level of the AMF1011-2 meets or exceeds a predetermined level (e.g., a minimum energy efficiency level defined by an energy management policy such as QoS requirements).

[0171] Furthermore, based on the determination that the energy efficiency level of AMF1011-2 does not meet or falls below a predetermined level, the server node may determine that the energy efficiency of AMF1011-2 needs to be improved or optimized. In this regard, the server node may determine one or more target energy efficiency factors that result in a certain level of energy efficiency, and may determine one or more operations to optimize one or more target energy efficiency factors.

[0172] For example, based on the determination that a low level of energy efficiency is caused by an overload of network traffic, the server node may determine one or more network entities (e.g., Wi-Fi, small cells, etc.) from which at least a portion of the network traffic load of the AMF1011-2 can be offloaded. As another example, based on the determination that a low level of energy efficiency is caused by a suboptimal operating mode (e.g., the load on the AMF1011-2 is low, but the AMF1011-2 is in a high-performance mode that consumes a large amount of energy), the server node may determine an operating mode (e.g., low-power mode, sleep mode, etc.) based on the current load information. It can be understood that the server node can appropriately determine one or more optimal configurations for other energy efficiency factors (e.g., network topology, resource management, etc.) described herein in a similar manner without departing from the scope of this disclosure.

[0173] When processing energy data, the server node may perform one or more energy management operations for managing the AMF1011-2 in a similar manner to those described above with reference to operation S830. According to one embodiment, the server node may output information to the AMF1011-2 (or one or more components hosting the AMF1011-2) that specifies one or more operations for optimizing one or more energy efficiency factors. Thus, the AMF1011-2 may utilize the information provided by the EMF1011-1 to optimize its energy consumption in order to optimize its energy efficiency. The EMF1011-1 may also be used to provide energy management to the SMF1011-3 and UPF1012-1 in a similar manner.

[0174] Referring still to Figure 10, the Session Management Function (SMF) 1011-3 may represent a network function responsible for managing and controlling the session-related aspects of a network entity (e.g., a UE). Key functions of the SMF 1011-3 may include, for example, session establishment (e.g., allocating network resources, setting up necessary controls and bearer paths, establishing a session context), separation of user plane and control plane (e.g., interacting with the control plane function (CPF) to handle control plane signaling and management while leaving the handling of user plane data to the user plane function (UPF)), policy and quality of service (QoS) enforcement (e.g., enforcing policies and QoS requirements set by the network operator or service provider, ensuring that appropriate QoS levels are applied to user sessions, ensuring that policies regarding data usage, traffic management, and service differentiation are enforced), and network slice management (e.g., coordinating network resource allocation, policies, and QoS parameters specific to network slices associated with a particular session).

[0175] Furthermore, User Plane Function (UPF) 1012-1 may represent a network function responsible for handling the user data plane in the network. Key functions of UPF 1012-1 may include, for example, data routing and forwarding (e.g., receiving user data packets from the SMF and routing them to their intended destinations), providing QoS management (e.g., applying QoS policies, managing the allocation of network resources to meet specified QoS requirements for user data traffic, controlling the delivery of data packets based on QoS parameters defined by SMF 1011-3), performing data processing tasks (e.g., data traffic shaping, data packet inspection, content filtering), and interworking with data networks (e.g., facilitating interworking and integration with external 3GPP networks and / or non-3GPP networks, handling protocol, format, or interface adaptation and conversion to enable seamless communication between networks).

[0176] A data network (DN) 1020-3 may include one or more networks, such as 3GPP networks and / or non-3GPP networks, involved in data transmission within a communications network ecosystem. For example, a data network represents a network infrastructure that enables data exchange between different network entities, such as UEs, network functions, and external networks. This infrastructure includes both 3GPP networks (e.g., core networks) and non-3GPP networks (external networks accessed through 3GPP networks). In addition, a data network may involve non-3GPP networks such as the Internet, private enterprise networks, or other external networks. These non-3GPP networks may be connected to 3GPP networks through interworking functions and gateways, enabling data exchange between the core network and external networks.

[0177] In short, SMF1011-3 and UPF1012-1 may be used to establish and manage user sessions, ensure appropriate QoS enforcement, handle data routing and forwarding, and enable efficient and secure data transmission between network entities. In this regard, the energy efficiency of SMF1011-3 and UPF1012-1 may be influenced by one or more energy efficiency factors (e.g., network traffic load, network topology, resource management configuration, operating mode, processing and computation load, etc.), as previously described with reference to AMF1011-2. In addition, the energy efficiency factors of SMF and UPF may further include data-related factors such as the following: • Data compression configuration and protocol: Data routed and transmitted via SMF1011-3 and UPF1012-1 may be compressed to reduce the data size for routing and transmission. Therefore, compression techniques and protocols that may affect the amount and size of data processed and transmitted may affect the energy consumption of SMF1011-3 and UPF1012-1 and thus affect their energy efficiency. • Data routing configuration: Configurations for routing data packets, such as routing decisions, routing cycles, and the amount and size of data per routing, can affect the energy consumption of SMF1011-3 and UPF1012-1.

[0178] The energy efficiency factors of SMF1011-3 and UPF1012-1 may be understood to further include any other suitable energy efficiency factors that may directly and / or indirectly affect the energy efficiency of SMF1011-3 and UPF1012-1 without departing from the scope of this disclosure.

[0179] Furthermore, SMF1011-3 may handle session management related to multiple UE1020-1s. In this case, when a server node utilizes EMF1011-1, it may communicate with SMF1011-3 (via the Nemf interface and / or Nsmf interface) to acquire and receive energy data related to at least one of the following: (1) each task performed by SMF1011-3 for all UEs, (2) each task performed by SMF1011-3 for a particular UE, and (3) the total energy consumption related to one or more tasks currently being performed by SMF1011-3. In addition or alternatively, when utilizing EMF1011-1, the server node may communicate with one or more OAM tools associated with SMF1011-3 to acquire and receive one or more of the above energy data.

[0180] For example, a server node may receive energy consumption E1 related to interaction with a decoupled data plane to manage data sessions for UE1020-1, energy consumption E2 related to PDU session management for UE1020-1, and energy consumption E3 related to managing the session context with UPF1012-1 for sessions initiated by UE1020-1. In another example, the server node may receive E1, E2, and E3 to manage sessions for all UEs connected to AN1020-2. In yet another example, the server node may receive energy consumption Etot related to all tasks currently being performed by SMF1011-3. It can be understood that the server node may be configured to receive any other energy data described herein in a similar manner.

[0181] Thus, the server node may utilize EMF1011-1 to perform one or more operations of Method 800 to provide energy management to SMF1011-3 and / or UPF1012-1 in a similar manner to that described above with reference to provisioning energy management to AMF1011-2.

[0182] In view of the above, the server node of the embodiment may interact with AMF1011-2, SMF1011-3, and UPF1012-1 and utilize EMF1011-1 to provide energy management for access, mobility, and session management operations. For example, when executing EMF1011-1 (or instructions related to EMF1011-1), the server node may automatically detect one or more target AMFs, SMFs, and UPFs whose energy needs to be managed. In this way, the server node may detect one or more optimal configurations for managing the target AMFs, SMFs, and / or UPFs in order to manage the target AMFs, SMFs, and UPFs. In this way, the energy consumed in operations related to the target AMFs, SMFs, and UPFs may be reduced, optimizing the energy efficiency of each target AMF, SMF, and UPF, and resulting in improved energy efficiency of the network system.

[0183] [Use Case Example 3: Energy Management of Network Repository Functionality] As described above, according to the embodiment, the server node may be configured to execute EMF (or related instructions) to interact with one or more network functions in provisioning energy management. Below is a description of one use case in which the EMF interacts with a network repository function (NRF) when providing energy management.

[0184] Figure 11 illustrates a block diagram of an example of a system configuration 1100 related to a third use case according to one or more embodiments. As illustrated in Figure 11, the system configuration 1100 may include an EMF 1110, multiple network entities 1120, and an NRF 1130. The EMF 1110 may be the same as the EMF described herein. The NRF 1130 may be one of the multiple network functions described herein, and the network entities 1120 may include the remaining network functions, UE, AN, etc., described herein.

[0185] The EMF1110, multiple network entities 1120, and NRF1130 may be coupled to each other in a communicative and operational manner via one or more appropriate communication interfaces such as SBIs as described herein. For example, the EMF1110 may communicate with network entity 1120 via a Nemf interface, network entity 1120 may communicate with NRF1130 via an Nnrf interface, and the EMF1110 may communicate with NRF1130 via a Nemf interface and / or an Nnrf interface.

[0186] In practice, the EMF1110, the multiple network entities 1120, and the NRF1130 may be hosted or deployed on one or more devices or equipment, such as one or more server nodes described herein. Thus, the communication and interoperation between the EMF1110, the multiple network entities 1120, and the NRF1130 may be presented or defined in relation to the communication and interoperation between the related devices / equipment. Similarly, the one or more operations that can be performed by the EMF1110 and NRF1130 described herein may be performed by the equipment, device, or equipment on which the EMF1110 and NRF1130 are hosted or deployed.

[0187] In this regard, the Network Repository Function (NRF) described herein may represent a component or network function responsible for managing network data and configuration information. For example, the NRF may be configured to manage data and information related to multiple network entities 1120. The energy efficiency of the NRF 1130 may be influenced by several energy efficiency factors, such as the following: • Data Storage and Acquisition Mechanisms: The efficiency of the data storage and acquisition mechanisms used by the NRF1130 may affect the energy efficiency of the NRF1130. For example, the energy consumption of the NRF1130 may be reduced by using optimized storage technologies such as solid-state drives (SSDs) or data compression technologies. Furthermore, the time and energy required to access network data may be reduced by using efficient data acquisition algorithms and caching mechanisms. • Data replication and distribution mechanisms: The mechanisms used by the NRF1130 to replicate and distribute network data across multiple network entities (e.g., across multiple NRF instances, across the NRF1130 and the database) can affect the energy efficiency of the NRF1130. For example, employing strategies such as intelligent data replication and placement may reduce the overhead of data transmission and retrieval, leading to lower energy consumption. • Data synchronization mechanism: The mechanism used by the NRF1130 to synchronize NRF instances and other network components may affect the energy efficiency of the NRF1130. Energy consumption of the NRF1130 may be reduced by minimizing unnecessary data synchronization and utilizing highly energy-efficient synchronization protocols. • Network Topology: The network topology and distribution of NRF instances can affect the energy efficiency of the NRF1130. Optimizing the placement of NRF instances may reduce data transmission distance, leading to lower energy consumption of the NRF1130. • Resource Management Configuration: The effects of resource management within the NRF1130, such as the intelligent utilization of storage and computing resources, may affect the energy efficiency of the NRF1130. Energy consumption of the NRF1130 may be reduced by optimizing resource allocation and usage.

[0188] The energy efficiency factor of NRF1130 may be understood to further include any other suitable energy efficiency factors that may directly and / or indirectly affect the energy efficiency of NRF1130 without departing from the scope of this disclosure.

[0189] In view of the foregoing, at least one processor of the server node may, when running EMF1110, receive energy data from multiple network entities 1120 and NRF1130 (and / or one or more associated OAM tools), and may perform one or more operations of Method 800 in a similar manner to those described above with reference to Use Cases 1 and 2 in order to process the received energy data and perform one or more energy management operations in order to optimize the energy efficiency of NRF1130.

[0190] [Use Case Example 4: Energy Information Exposure] As described above, according to the embodiment, a server node may execute an EMF (or related instruction) to share, publish, or expose energy-related information, such as energy consumption information and energy efficiency level information, to one or more network entities. Below is a description of a use case in which an EMF interacts with a network exposure function (NEF) when exposing energy information.

[0191] Figure 12 illustrates a block diagram of an example of a system configuration 1200 related to a fourth use case according to one or more embodiments. As illustrated in Figure 12, the system configuration 1200 may include an EMF 1210, multiple network entities 1220, an NEF 1230, and a trusted third party 1240. The EMF 1210 may be the same as the EMF described herein. The NEF 1230 and the trusted third party 1240 may be part of the multiple network entities described herein, and the network entity 1220 may include the remaining network functions, UEs, ANs, etc. described herein. The OAM tool 1250 may represent one or more OAM tools described herein.

[0192] EMF1210, multiple network entities 1220, NEF1230, and trusted third parties 1240 may be coupled to each other in a communicative and operational manner via one or more appropriate communication interfaces such as SBIs described herein. For example, EMF1210 may communicate with network entity 1220 via a Nemf interface, EMF1210 may communicate with NEF1230 via a Nemf interface and / or an Nnef interface, and NEF1230 may communicate with trusted third parties 1240 via an Nnef interface. OAM tool 1250 may be coupled to network entities 1220 and NEF1230 in a communicative manner and may be configured to perform one or more measurements (e.g., energy measurements, performance measurements) on them continuously (or periodically). Thus, OAM tool 1250 may provide EMF1210 with energy data related to network entities 1220 and / or NEF1230 in response to a request from EMF1210.

[0193] In practice, one or more of the EMF1210, the multiple network entities 1220, the NEF1230, and the trusted third party 1240 may be hosted or deployed in one or more devices, equipment, or apparatus, such as one or more server nodes described herein. Thus, the communication and interoperation between the EMF1210, the multiple network entities 1220, the NEF1230, and the trusted third party 1240 may be understood as being presented or defined in relation to the communication and interoperation between the relevant devices, equipment, or apparatus. Similarly, one or more operations that can be performed by the EMF1210 and NEF1230 described herein may be performed by the devices, equipment, or apparatus on which the EMF1210 and NEF1230 are hosted or deployed.

[0194] In this regard, the NEF1230 described herein may represent a network function that utilizes a network architecture (e.g., a 3GPP network architecture such as a 5G network architecture or a 6G network architecture) to enable exposure of energy information within the network. That is, the NEF1230 enables one or more authorized third parties (e.g., third-party applications, systems, devices, etc.) to access energy information. The energy efficiency of the NEF1230 may be influenced by several energy efficiency factors, such as the following: • Network Traffic Load: The amount of network traffic handled by the NEF1230 can affect its energy efficiency. For example, a higher traffic load requires more processing power and resources, leading to increased energy consumption of the NEF1230. Energy use in the NEF1230 may be optimized by utilizing efficient load balancing techniques and capacity planning. • Resource Management Configuration: The energy efficiency of the NEF1230 may be improved by utilizing effective resource management within the NEF1230, such as intelligent utilization of computing and network resources. Optimizing resource allocation, scaling, and usage in this way may reduce the energy consumption of the NEF1230 and improve its energy efficiency. • Data Processing and Filtering Mechanisms: The efficiency of the data processing and filtering mechanisms used by the NEF1230 may affect its energy efficiency. By utilizing optimized algorithms and techniques for data processing, filtering, and aggregation, the energy consumed during data processing and filtering may be reduced, resulting in lower energy consumption and improved energy efficiency of the NEF1230. • Security Mechanisms: The security mechanisms implemented in the NEF1230 may affect its energy efficiency. For example, the encryption, authentication, and authorization processes when communicating with trusted third parties require computing resources and may affect the energy consumption of the NEF1230. Therefore, efficient security algorithms and optimized authentication mechanisms may reduce energy overhead and improve the energy efficiency of the NEF1230. • Protocol Optimization Mechanism: The energy efficiency of the NEF1230 may be improved by optimizing the protocols and data formats used by the NEF1230. For example, an efficient protocol can reduce the amount of data transmitted and processed, resulting in lower energy consumption for the NEF1230. • Operating state or mode: The energy efficiency of the NEF1230 may be improved by implementing a sleep mode or low-power state during periods of inactivity. The NEF1230 can conserve energy by entering a low-power mode when there are no active requests or data processing.

[0195] The energy efficiency factor of NEF1230 may be understood to further include any other suitable energy efficiency factors that may directly and / or indirectly affect the energy efficiency of NEF1230, without departing from the scope of this disclosure.

[0196] In view of the above, at least one processor of the server node may, when utilizing the EMF1210, receive energy data from multiple network entities 1220 and / or NEF1230 (and / or from the OAM tool 1250), and may perform one or more operations of Method 800 in a similar manner to those described above with reference to Use Cases 1 and 2 in order to process the received energy data and perform one or more energy management operations to optimize the energy efficiency of the NEF1230. Subsequently, the energy information may be exposed to a trusted third party 1240 via the NEF1230.

[0197] Thus, energy information and data may be provided to one or more network entities or users in an energy-efficient manner. For example, energy information such as the percentage of renewable energy related to a dedicated network slice may be provided periodically to a trusted third party. Specifically, the percentage of renewable energy used to provide dedicated communication services to a trusted third party may be tracked over time and compiled for reporting to the trusted third party. The reporting period may be defined, for example, monthly or annually. In such a case, the server node may store information regarding the percentage of renewable energy used to provide dedicated communication services to a trusted third party in one or more storage media (e.g., storage 620, database 730, etc.) and transmit the same information to the trusted third party on request or automatically based on the reporting period.

[0198] As another example, a server node may forward energy information of one or more network entities (e.g., information on energy consumption and energy efficiency levels) to one or more UEs of one or more related users. Thus, energy information that may define the energy efficiency of the network system as a whole or as individual network entities may be provided to related users, enabling them to make appropriate decisions about their service providers and usage patterns. For example, a user may request a live stream of content (e.g., a live cricket match), and the energy efficiency level of the network system in providing the requested content may be displayed on the user's UE. The user may choose to continue watching the requested live stream content, or they may choose not to depend on the energy efficiency level.

[0199] [Example of reference point representation] The implementation of EMF in the embodiment was previously described with reference to a service-based architecture (SBA) that enables decoupling of network functions, promotes service-oriented design, and facilitates flexible service deployment and orchestration. Generally, SBAs are based on a modular and distributed approach in which network functions are designed as self-contained services that communicate with each other through service-based interfaces (SBIs). As previously described, the functionality of EMF in the embodiment may be provided to network entities via a dedicated SBI, which is described here as the “Nemf” interface.

[0200] In some embodiments, embodiments of the EMF of this disclosure may be presented in a reference point representation for other perspectives on the integration of the EMF in a network system. Figure 13 illustrates a block diagram of an example of a reference point presentation 1300 of a network system in which the EMF is implemented according to one or more embodiments. The EMF1310, AMF1320, SMF1330, and NRF1340 in Figure 13 may be the same as those described above with reference to Figures 1 to 12. For this reason, redundant descriptions related thereto may be omitted below for simplicity.

[0201] As illustrated in Figure 13, at least three new reference point representations (i.e., N110, N111, and N112) may be introduced with the integration of the EMF1310. In practice, the labeling of these three new reference point representations may be expressed in any other appropriate terminology without departing from the scope of this disclosure.

[0202] In practice, AMF1320, SMF1330, and NRF1340 may be communicatively coupled to other network functions via other existing reference point representations (e.g., N1, N2, N3, N4, N6, N9, N11, N12, N14, N15, etc.), and EMF1310 may be communicatively coupled to the aforementioned other network functions via AMF1320, SMF1330, and NRF1340.

[0203] The reference point representation "N110" illustrates the interaction between the EMF1310 and the SMF1330. The reference point representation "N110" enables the EMF1310 to communicate with the SMF1330 and to manage and control the energy usage associated with the SMF1330 (or any other network entity that is communicably coupled to the EMF1310 via the SMF1330).

[0204] Similarly, reference point expression "N111" illustrates the interaction between EMF1310 and AMF1320. Thus, reference point expression "N111" enables EMF1310 to communicate with AMF1320 and to manage and control energy usage related to AMF1320 (or any other network entity that is communicably coupled to EMF1310 via AMF1320). Reference point expression "N112" illustrates the interaction between EMF1310 and NRF1340. Reference point expression "N112" enables EMF1310 to communicate with NRF1340 and to manage and control energy usage related to NRF1340 (or any other network entity that is communicably coupled to EMF1310 via NRF1340).

[0205] In light of the foregoing, the introduction of these new reference points N110, N111, and N112 not only ensures that the EMF of this disclosure can be effectively integrated into existing and future communication network systems to manage the energy consumption of network entities, but also provides extensive interaction with other key network entities (e.g., key network functions). This extensive interconnectivity is important for the EMF to have a systematic impact and optimize energy efficiency and sustainability across the entire network system (e.g., a 5G network).

[0206] [Various aspects of the embodiment] Referring to Figures 1 to 13, the embodiments described herein are merely examples of possible embodiments of the present disclosure and are not intended to limit or restrict the scope of the present disclosure.

[0207] Specifically, the foregoing disclosures provide examples and descriptions, but are not intended to be exhaustive or to limit implementations to the exact forms disclosed. Modifications and variations are possible in light of the foregoing disclosures or may be obtained from the implementation.

[0208] Some embodiments may also relate to apparatus or devices (e.g., server nodes), systems, methods, and / or computer-readable media at any possible level of technical detail of integration. Furthermore, one or more of the above components may be implemented as instructions that are stored on computer-readable media and are executable by at least one processor (and / or may include at least one processor). The computer-readable media may include computer-readable non-temporary storage media (or media) that stores computer-readable program instructions for causing the processor to perform operations.

[0209] A computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer-readable storage medium may, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital multipurpose disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or grooves on which instructions are recorded, or any suitable combination thereof. The computer-readable storage medium used herein is not to be interpreted as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmitting media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0210] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and transfers them to storage in the computer-readable storage medium within each computing / processing device.

[0211] Computer-readable program code / instructions for performing an operation may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk and C++, procedural programming languages ​​such as the C programming language, or similar programming languages.

[0212] Computer-readable program instructions may be executed as a standalone software package, either entirely on the user's computer, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or wide area network (WAN), and the connection may be made to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, for example, electronic circuits including programmable logic circuits, FPGAs (field-programmable gate arrays), or programmable logic arrays (PLAs) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuits in order to perform lateral or operational tasks.

[0213] These computer-readable program instructions may be provided to a general-purpose computer, a dedicated computer, or a processor of another programmable data processing device to generate a device such that instructions executed via the processor of a computer or other programmable data processing device generate means for implementing functions / actions described in flowcharts and / or block diagrams (one or more blocks). These computer-readable program instructions may be stored on a computer-readable storage medium on which the instructions are stored, which can be instructed to make a computer, a programmable data processing device, and / or other device function in a particular manner such that the storage medium containing the instructions has a creation containing instructions that implement aspects of functions / actions described in flowcharts and / or block diagrams (one or more blocks).

[0214] Computer-readable program instructions may be loaded onto a computer, another programmable device, or another device so that a series of operational steps are executed on the computer, another programmable device, or other device to generate a computer-implemented process in which instructions executed on the computer, another programmable device, or other device implement a function / action described in a flowchart and / or block diagram (one or more blocks).

[0215] The illustrated flowcharts and block diagrams illustrate the architecture, functions, and operations of possible implementations of systems, methods, and computer-readable media according to various embodiments. Here, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, comprising one or more executable instructions for implementing a particular logical function. Methods, computer systems, and computer-readable media may include additional blocks, fewer blocks, different blocks, or different arrangements of blocks than those shown in the diagrams. In some alternative implementations, the functions shown in the blocks may occur outside the order shown in the diagrams. For example, two blocks shown consecutively may actually be executed simultaneously or substantially simultaneously, depending on the functions involved, or the blocks may be executed in reverse order. Each block in the illustrated block diagrams and / or flowcharts, and combinations of blocks in the illustrated block diagrams and / or flowcharts, may be implemented by a system based on dedicated hardware that performs a particular function or action, or by executing a combination of dedicated hardware and computer instructions.

[0216] It is evident that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, or combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limited to the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It is understood that software and hardware may be designed to implement the systems and / or methods based on the descriptions herein.

[0217] In view of the foregoing, various further aspects and features of the embodiments of this disclosure may be defined by the following items. Item 1: A device including an energy management function (EMF) for communication networks. The aforementioned device is Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. The EMF may be configured to execute instructions in order to implement the EMF to perform the above. Item 2: The one or more operations for managing the energy usage of the at least one network entity are: Sharing information on the energy efficiency level with one or more users, Sharing information on the energy efficiency level with one or more trusted third parties, Managing one or more resources related to the at least one network entity, To manage one or more operations related to at least one network entity, The management of the state of at least one network entity, Managing one or more energy standards related to at least one network entity, The apparatus described in item 1, which may include one or more of the above. Item 3: The aforementioned EMF may also be the core network function of the communication network. The aforementioned at least one network entity may include one or more of at least one network function, at least one user device, and at least one access network. The device described in item 1 or 2. Item 4: The apparatus described in item 3, wherein the at least one network function may include one or more of the following: network data analysis function (NWDAF), access and mobility management function (AMF), session management function (SMF), network repository function (NRF), and network exposure function (NEF). Item 5: The device may be configured to execute the command for receiving the one or more energy data from the at least one network entity via a service-based interface (SBI) related to the EMF. The EMF may expose its associated energy management functions via the SBI. The device described in any of items 1 through 4. Item 6: The apparatus according to any one of items 1 to 5, which may be configured to execute the command for receiving the one or more energy data from the at least one network entity via at least one interface defined by at least one reference point representation. Item 7: The apparatus according to any one of items 1 to 6, wherein the one or more energy data may include one or more energy consumption information, energy profiles, energy metrics, network information, component status, forecast data, and one or more energy efficiency factors. Item 8: The apparatus according to item 7, wherein the prediction data may include one or more predictions of future energy use patterns and network traffic. Item 9: The apparatus described in item 7 or 8, wherein the one or more energy efficiency factors may include one or more network traffic load, network topology, resource management, operating mode, routing and handover algorithms, processing and computation load, network protocol configuration, data compression configuration and protocol, data routing configuration, data storage and acquisition mechanism, data replication and distribution mechanism, data synchronization mechanism, data processing and filtering mechanism, and security mechanism. Item 10: The device described in any of items 1 to 9 may include an edge server. Item 11: Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. Includes, A method implemented by an Energy Management Function (EMF) for communication networks. Item 12: The one or more operations for managing the energy usage of the at least one network entity are: Sharing information on the energy efficiency level with one or more users, Sharing information on the energy efficiency level with one or more trusted third parties, Managing one or more resources related to the at least one network entity, To manage one or more operations related to at least one network entity, The management of the state of at least one network entity, Managing one or more energy standards related to at least one network entity, The method described in item 11, which may include one or more items. Item 13: The aforementioned EMF may also be the core network function of the communication network. The aforementioned at least one network entity may include one or more of at least one network function, at least one user device, and at least one access network. The method described in item 11 or 12. Item 14: The method according to item 13, wherein the at least one network function may include one or more of the following: network data analysis function (NWDAF), access and mobility management function (AMF), session management function (SMF), network repository function (NRF), and network exposure function (NEF). Item 15: Receiving the one or more energy data may include receiving the one or more energy data from at least one network entity via a Service-Based Interface (SBI) associated with the EMF. The EMF may expose its associated energy management functions via the SBI. The method described in any of items 11 through 14. Item 16: The method according to any one of items 11 to 15, wherein receiving the one or more energy data may include receiving the one or more energy data from the at least one network entity via at least one interface defined by at least one reference point representation. Item 17: The method according to any one of items 11 to 16, wherein the one or more energy data may include one or more energy consumption information, energy profiles, energy metrics, network information, component status, forecast data, and one or more energy efficiency factors. Item 18: The method according to item 17, wherein the prediction data may include one or more predictions of future energy use patterns and predictions of network traffic. Item 19: The method described in item 17 or 18, wherein the one or more energy efficiency factors may include one or more network traffic load, network topology, resource management, operating mode, routing and handover algorithms, processing and computation load, network protocol configuration, data compression configuration and protocol, data routing configuration, data storage and retrieval mechanism, data replication and distribution mechanism, data synchronization mechanism, data processing and filtering mechanism, and security mechanism. Item 20: A non-temporary, computer-readable recording medium that stores instructions for implementing energy management functions (EMF) for communication networks. Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. To cause the device to perform a method that includes, The aforementioned instructions may be executable by the device.

[0218] In light of the above teachings, it can be understood that many modifications and alterations of this disclosure are possible. It is clear that, within the scope of the attached items, this disclosure may be implemented in a manner different from that specifically described herein.

Claims

1. Equipped with energy management functions (EMF) for communication networks, Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. A device configured to execute instructions in order to implement the EMF to perform the above.

2. The one or more operations for managing the energy usage of the at least one network entity are: Sharing information on the energy efficiency level with one or more users, Sharing information on the energy efficiency level with one or more trusted third parties, Managing one or more resources related to at least one network entity, To manage one or more operations related to at least one network entity, The management of the state of at least one network entity, Managing one or more energy standards related to at least one network entity, The apparatus according to claim 1, comprising one or more of the above.

3. The aforementioned EMF is the core network function of the communication network, The said at least one network entity comprises one or more of at least one network function, at least one user device, and at least one access network. The apparatus according to claim 1.

4. The apparatus according to claim 3, wherein the at least one network function comprises one or more of the following: network data analysis function (NWDAF), access and mobility management function (AMF), session management function (SMF), network repository function (NRF), and network exposure function (NEF).

5. The device is configured to execute the command for receiving the one or more energy data from the at least one network entity via a service-based interface (SBI) related to the EMF. The EMF exposes its associated energy management functions via the SBI. The apparatus according to claim 1.

6. The apparatus according to claim 1, configured to execute the command for receiving the one or more energy data from the at least one network entity via at least one interface defined by at least one reference point representation.

7. The apparatus according to claim 1, wherein the one or more energy data comprises one or more energy consumption information, energy profiles, energy metrics, network information, component status, forecast data, and one or more energy efficiency factors.

8. The apparatus according to claim 7, wherein the prediction data comprises one or more predictions of future energy use patterns and network traffic.

9. The apparatus according to claim 7, wherein the one or more energy efficiency factors include one or more network traffic load, network topology, resource management, operating mode, routing and handover algorithm, processing and computation load, network protocol configuration, data compression configuration and protocol, data routing configuration, data storage and acquisition mechanism, data replication and distribution mechanism, data synchronization mechanism, data processing and filtering mechanism, and security mechanism.

10. The apparatus according to claim 1, further comprising an edge server.

11. Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. Equipped with, A method implemented by an energy management function (EMF) for communication networks.

12. The one or more operations for managing the energy usage of the at least one network entity are: Sharing information on the energy efficiency level with one or more users, Sharing information on the energy efficiency level with one or more trusted third parties, Managing one or more resources related to at least one network entity, To manage one or more operations related to at least one network entity, The management of the state of at least one network entity, Managing one or more energy standards related to at least one network entity, The method according to claim 11, comprising one or more of the above.

13. The aforementioned EMF is the core network function of the communication network, The said at least one network entity comprises one or more of at least one network function, at least one user device, and at least one access network. The method according to claim 11.

14. The method according to claim 13, wherein the at least one network function comprises one or more of the following: network data analysis function (NWDAF), access and mobility management function (AMF), session management function (SMF), network repository function (NRF), and network exposure function (NEF).

15. Receiving the one or more energy data comprises receiving the one or more energy data from at least one network entity via a Service-Based Interface (SBI) related to the EMF, The EMF exposes its associated energy management functions via the SBI. The method according to claim 11.

16. The method according to claim 11, wherein receiving the one or more energy data comprises receiving the one or more energy data from the at least one network entity via at least one interface defined by at least one reference point representation.

17. The method according to claim 11, wherein the one or more energy data comprises one or more energy consumption information, energy profiles, energy metrics, network information, component status, forecast data, and one or more energy efficiency factors.

18. The method according to claim 17, wherein the prediction data comprises one or more predictions of future energy use patterns and predictions of network traffic.

19. The method according to claim 17, wherein the one or more energy efficiency factors include one or more network traffic load, network topology, resource management, operating mode, routing and handover algorithms, processing and computation load, network protocol configuration, data compression configuration and protocol, data routing configuration, data storage and acquisition mechanism, data replication and distribution mechanism, data synchronization mechanism, data processing and filtering mechanism, and security mechanism.

20. A non-temporary computer-readable recording medium that records instructions for implementing energy management functions (EMF) for a communication network, Receiving one or more energy data related to at least one network entity from at least one network entity, Processing the one or more energy data to generate an energy efficiency level associated with at least one network entity, To manage the energy use of at least one network entity based on the energy efficiency level, one or more operations are performed. To cause the device to perform a method that includes, The aforementioned instruction is a non-temporary computer-readable recording medium that can be executed by the aforementioned device.

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