WO2022058049A1 - Energy efficiency-based network function discovery and selection - Google Patents

Energy efficiency-based network function discovery and selection Download PDF

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Publication number
WO2022058049A1
WO2022058049A1 PCT/EP2021/054331 EP2021054331W WO2022058049A1 WO 2022058049 A1 WO2022058049 A1 WO 2022058049A1 EP 2021054331 W EP2021054331 W EP 2021054331W WO 2022058049 A1 WO2022058049 A1 WO 2022058049A1
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Prior art keywords
network
entity
network entity
information
energy efficiency
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PCT/EP2021/054331
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French (fr)
Inventor
Miguel Angel PUENTE PESTAÑA
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Telefonaktiebolaget Lm Ericsson (Publ)
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Publication of WO2022058049A1 publication Critical patent/WO2022058049A1/en

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
    • H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/04—Processing captured monitoring data, e.g. for logfile generation

Definitions

  • the present invention generally relates to the fields of energy efficiency, and more specifically, the invention relates to NF and NF service discovery and selection mechanisms to reduce the energy consumption in a mobile network.
  • the NWDAF Network Data Analytics Function
  • 5GC First Generation Core
  • NFs Network Functions
  • OAM Operations and Management
  • Analytics information are either statistical information of past events, or predictive information.
  • Different NWDAF instances may be present in the 5GC, with possible specializations per type of analytics.
  • the capabilities of a NWDAF instance are described in the NWDAF profile stored in the NRF (Network Repository Function).
  • NRF Network Repository Function
  • Each NWDAF instance should provide the list of Analytics Identifiers (ID) that it supports when registering to the NRF, in addition to other NRF registration elements of the NF (Network Function) profile.
  • ID Analytics Identifiers
  • NWDAF Network-to-Network Interface
  • Other NFs requiring the discovery of an NWDAF instance that provides support for some specific type of analytics may query the NRF and include the Analytics I D(s) that identifies the desired type of analytics for that purpose.
  • the Network Repository Function is the entity in charge of Network Function (NF) and NF service discovery and selection.
  • 3GPP TS 29.510 specifies that NF or NF service selection is based on information contained in the NFProfile resp. NFService data structures stored in NRF.
  • the fields that are used for the NF or NF service selection decision are the priority, capacity and load.
  • Priority is the priority relative to other NFs of the same type to be used for NF selection.
  • Capacity is the static capacity information, which can be expressed as an absolute value or as a relative value with respect to the capacity of other NF instances of the same type.
  • Load is dynamic load information that indicates the current load percentage of the NF.
  • the load, capacity and priority parameters are used for NF selection and load balancing.
  • a Management Data Analytics Service provides data analytics of different network related parameters including for example load level and/or resource utilisation.
  • the MDAS for a network function can collect the NF's load related performance data, e.g. resource usage status of the NF.
  • the analysis of the collected data may provide forecast of resource usage information in a predefined future time. This analysis may also recommend appropriate actions, e.g. scaling of resources, admission control, load balancing of traffic, etc.
  • a MDAS for a network slice instance (NSI) provides NSI related data analytics.
  • the service may consume the corresponding MDAS of its constituent NSSI(s).
  • the NSI MDAS may further classify or shape the data in different useful categories according to different customer needs, e.g. slice load, constituent NSSI load, communication service loads. This data can be used for further analysis e.g. resource usage prediction, failure prediction for an NSI, etc.
  • a Management Data Analytics Function provides the Management Data Analytics Service for one or more NF, NSSI and/or NSI, and may consume some management services produced by other functional blocks.
  • MDAS can be deployed at different levels, for example, at domain level (e.g. RAN, CN, NSSI) or in a centralized manner (e.g. in a PLMN level).
  • a domain-level MDAS provides domain specific analytics, e.g. resource usage prediction in a CN or failure prediction in a NSSI, etc.
  • a centralized MDAS can provide end-to-end or cross-domain analytics service, e.g. resource usage or failure prediction in an NSI, optimal CN node placement for ensuring lowest latency in the connected RAN, etc.
  • a problematic aspect is that current 3GPP solutions do not allow for NF or NF service discovery and selection aiming at selecting the NF resp. NF services that are more energy efficient, and thus minimizing the energy consumption in the operator's network.
  • Current NF or NF service selection solutions are based on the priority, capacity and load information stored in NRF (NFProfile resp. NFService data structures). But none of these parameters give any information on the energy efficiency of the NFs or NF services to be selected.
  • a further problematic aspect is that current 3GPP specs do not provide any solution on how to obtain the energy efficiency of the different NF or NF service implementations.
  • An object of the invention is to reduce the energy consumed by a mobile network.
  • a first aspect of the invention relates to a method performed by a network data analytics entity for providing energy efficiency information of a first network entity.
  • the method includes receiving from the first network entity or a second network entity, energy consumption information of the first network entity; determining the energy efficiency information of the first network entity based on the energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity.
  • the receiving step further comprises receiving computing resources usage information of the first network entity, and wherein the usage level information used in the determining step comprises the computing resources usage information of the first network entity.
  • the receiving step further comprises receiving information on the number of users allocated to the first network entity, and wherein the usage level information used in the determining step comprises the number of users allocated to the first network entity.
  • the method further comprises transmitting to the first network entity or the second network entity, a request to collect energy consumption information of the first network entity, computing resources usage information of the first network entity and/or information on the number of users allocated to the first network entity.
  • the method further comprises receiving from the third network entity a request for energy efficiency information analytics of the first network entity.
  • the first network entity is a Network Function, NF, or a NF service.
  • the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system.
  • the third network entity is a network repository entity or a service discovery entity.
  • a second aspect of the invention relates to a method performed by a first network entity for providing energy efficiency information of said first network entity. The method includes determining the energy efficiency information of the first network entity based on energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity.
  • the method further includes receiving from a second network entity the energy consumption information and usage level information of the first network entity.
  • the usage level information comprises computing resources usage information of the first network entity.
  • the method further comprises receiving from the second network entity the computing resources usage information of the first network entity.
  • the method further comprises transmitting to the second network entity, a request to collect energy consumption information of the first network entity and/or computing resources usage information of the first network entity.
  • the first network entity is a Network Function, NF, or a NF service.
  • the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system.
  • the third network entity is a network repository entity or a service discovery entity.
  • a third aspect of the invention relates to a method performed by a network repository entity for discovering network entities.
  • the method includes receiving the energy efficiency information of a first network entity; receiving from a second network entity a discovery request matching the first network entity; performing the discovery and selection of the first network entity based on the energy efficiency information of the first network entity; and transmitting to the second network entity a discovery response including the network address of the first network entity.
  • the method further includes transmitting to a network data analytics entity a request for energy efficiency information analytics of the first network entity, and wherein the energy efficiency information of the first network entity is received from said network data analytics entity.
  • the energy efficiency information of the first network entity is received from the first network entity in a registration request or registration update message.
  • the discovery of the first network entity is performed together with the discovery of other network entities matching the discovery request, and the discovery response further includes the network addresses of the other network entities, the energy efficiency information of the first network entity and the energy efficiency information of the other network entities.
  • the first network entity is a Network Function, NF, or a NF service.
  • the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system.
  • the third network entity is a network repository entity or a service discovery entity.
  • a fourth aspect of the invention relates to a method performed by a network entity for discovering and selecting other network entities based on energy efficiency information.
  • the method includes transmitting to a network repository entity a discovery request for a network entity of a certain type; receiving from the network repository entity a discovery response including a set of discovered network entities together with their energy efficiency information; and selecting one of the network entities based on its energy efficiency information.
  • mobile network nodes particularly a network data analytics entity, a network entity and a network repository entity, each configured to perform the respective methods as described herein.
  • the network data analytics entity is a Network Data Analytics Function (NWDAF) 115
  • the network repository entity is a Network Repository Function (NRF) 110
  • the network entity is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the solution disclosed herein enables mobile network operators to reduce the cost of the network operation by means of reducing the energy consumption of the mobile network.
  • the solution disclosed herein allows to select NFs deployed in more energy efficient cloud infrastructures, as the derived efficiency parameter includes the effects of both the NF's implementation and the cloud resources the NFs are deployed over.
  • FIG. 1 is a networked system in accordance with particular embodiments of the solution described herein;
  • Figure 2 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
  • Figure 3 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
  • Figure 4 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
  • Figure 5 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
  • Figure 6 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
  • Figure 7 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
  • Figure 8 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
  • Figure 9 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
  • FIG. 10 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
  • FIG 11 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
  • Figure 12 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
  • Figure 13 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
  • Figure 1 is an example networked system 100 in accordance with example embodiments of the present disclosure.
  • Figure 1 specifically illustrates User Equipment (UE) 101, which may be in communication with a (Radio) Access Network (RAN) 102 and Access and Mobility Management Function (AMF) 106 and User Plane Function (UPF) 103.
  • the AMF 106 may, in turn, be in communication with core network services including Session Management Function (SMF) 107 and Policy Control Function (PCF) 111.
  • SMF Session Management Function
  • PCF Policy Control Function
  • the core network services may also be in communication with an Application Server/ Application Function (AS/AF) 113.
  • AS/AF Application Server/ Application Function
  • Networked services also include Network Slice Selection Function (NSSF) 108, Authentication Server Function (AUSF) 105, User Data Management (UDM) 112, Network Exposure Function (NEF) 109, Network Repository Function (NRF) 110, User Data Repository (UDR) 114, Network Data Analytics Function (NWDAF) 115 and Data Network (DN) 104.
  • NMF Network Exposure Function
  • NRF Network Repository Function
  • NWDAF Network Data Analytics Function
  • DN Data Network
  • an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108 are each considered to be an NF.
  • One or more additional instances of these network functions (NF) may be incorporated into the networked system.
  • the solution described herein aims to reduce the energy consumed by a mobile network.
  • this disclosure provides a method performed by a network data analytics entity, a network repository entity, and other network entities (specifically a first, a second and a third network entity).
  • the network data analytics entity is a NWDAF 115.
  • the network repository entity is an NRF 110.
  • the other network entities are NFs or NF services. The proposed solution applies to both NFs and NF services.
  • the method comprises receiving, at the network data analytics entity from the network repository entity, a request for energy efficiency information analytics of a first network entity; transmitting from the network data analytics entity to the first network entity or a second network entity, a request to collect energy consumption information of the first network entity, computing resource usage information of the first network entity and/or information on the number of users allocated to the first network entity; receiving, at the network data analytics entity from the first network entity or the second network entity, energy consumption information of the first network entity, computing resources usage information of the first network entity and/or the number of users allocated to the first network entity; determining, at the network data analytics entity, the energy efficiency information of the first network entity based on the energy consumption information of the first network entity, computing resource usage information of the first network entity and/or the number of users allocated to the first network entity; and transmitting from the network data analytics entity the determined energy efficiency information of the first network entity to a third network entity.
  • the method may also comprise determining, at the first network entity, the energy efficiency information of the first network entity based on energy consumption information of the first network entity, computing resources usage information of the first network entity and/or the number of users allocated to the first network entity; and transmitting from the first network entity the determined energy efficiency information of the first network entity to the network repository entity.
  • the method further comprises receiving at the network repository entity the energy efficiency information of a first network entity; receiving at the network repository entity from a second network entity a discovery request matching the first network entity; performing at the network repository entity the discovery and selection of the first network entity based on the energy efficiency information of the first network entity; and transmitting from the network repository entity to the second network entity a discovery response including the network address of the first network entity.
  • the first network entity is a Network Function, NF, or a NF service.
  • the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF 113, or an energy consumption monitoring system.
  • the third network entity is a network repository entity or a service discovery entity, more specifically an NRF 110.
  • the NF can be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the method comprises including a new parameter in the NFProfile/NFService in NRF 110, so called "efficiency", denoting how efficient in terms of energy consumption is the corresponding NF or NF service.
  • This parameter can be specified in relative terms among NFs/NF services (as the priority or capacity parameters are currently specified) or as an absolute value (e.g. in terms of energy consumed per user, or energy consumed per executed computing instruction, etc.)
  • the method comprises deriving the "efficiency” using the analytics capabilities of the Core Network (NWDAF) and OSS (MDAF).
  • NWDAF may collect the following information on a per NF/NF service basis over a certain timespan:
  • Activity level Indicative of the level of activity of the NF/NF service, e.g. number of actions triggered, number of processes executed, number of interactions with other entities (requests/responses, notifications), etc.
  • NWDAF may also collect the absolute computing load and energy consumption from other entities within OSS, for example the absolute computing load from the orchestrator and the energy consumption from an energy monitoring entity measuring the amount of electric energy consumed by the cloud resources (e.g. NFs). This entity may aggregate all energy used in a data center (e.g. servers, cooling, etc.) and extract statistics on the energy consumed per cloud resource.
  • entities within OSS, for example the absolute computing load from the orchestrator and the energy consumption from an energy monitoring entity measuring the amount of electric energy consumed by the cloud resources (e.g. NFs).
  • This entity may aggregate all energy used in a data center (e.g. servers, cooling, etc.) and extract statistics on the energy consumed per cloud resource.
  • the NRF 110 can request/subscribe to the efficiency analytics in NWDAF for a concrete NF/NF service.
  • a consumer NF/NF service can discover NFs/NF services based on energy efficiency optimization objectives, for example by sending an indication to NRF to retrieve the most energy efficient NFs/NF services, or by receiving the efficiency values in the NFProfile/NFService and selecting the most efficient ones locally in the consumer NF/NF service.
  • the definition of the NFProfile (and NFService) data structures in NRF may be extended as follows:
  • This disclosure also provides mobile network nodes, particularly a network data analytics entity 1000, a network entity 1100, and a network repository entity 1200 and a further network entity 1300, each configured to perform the respective methods as described herein.
  • the network data analytics entity 1000 is a NWDAF 115
  • the network repository entity 1200 is an NRF 110
  • the network entities 1100 and 1300 are any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the solution disclosed herein enables mobile network operators to reduce the cost of the network operation by means of reducing the energy consumption of the mobile network.
  • the solution disclosed herein allows to select NFs deployed in more energy efficient cloud infrastructures, as the derived efficiency parameter includes the effects of both the NF's implementation and the cloud resources the NFs are deployed over.
  • Figure 2 is a signaling diagram illustrating a procedure for providing the energy efficiency of a network entity.
  • the procedure is performed by a network data analytics entity, a network repository entity, an Operations Support System (OSS) 202, and the network entity.
  • the network data analytics entity is a NWDAF 115
  • the network repository entity is an NRF 110
  • the network entity is a NF 201.
  • the NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the NRF subscribes to NWDAF for energy efficiency analytics of a NF, including an indication of the efficiency analytics, for example as an Event-ID, and the NF-ID.
  • the NWDAF sends to the OSS a request to get energy consumption information of the NF, including the NF-ID.
  • the message may include the timespan the NWDAF is interested in, and the reporting information for the reports (e.g. desired periodicity, etc.).
  • the OSS is a Cloud Orchestrator, a management data analytics entity (for example an MDAF), an Application Function (AF 113) or an energy consumption monitoring system.
  • a management data analytics entity for example an MDAF
  • AF 113 an Application Function
  • an energy consumption monitoring system for example an energy consumption monitoring system.
  • the OSS sends to the NWDAF an energy consumption report for the NF including the NF-ID, the energy consumption, e.g. in terms of Jules, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
  • NWDAF sends to the OSS a request or subscription request for computing resources usage information of a NF, including the NF-ID.
  • the message may include the timespan the NWDAF is interested in, and the reporting information for the reports (e.g. desired periodicity, etc.).
  • the OSS sends to the NWDAF a computing resources usage information report including the NF-ID, the computing resources usage information, e.g. number of executed instructions, CPU cycles, etc., and optionally, a timespan or timestamp pertaining to the computing resources usage information.
  • the NWDAF may get the number of UEs allocated to the NF by sending a request to the NF.
  • this step can be done via standard mechanisms, e.g. querying UDR for the users allocated to SMF or AMF, querying SMF for the users allocated to UPF, etc.
  • the NWDAF receives the information on the number of users allocated to the NF.
  • this message may also include the activity level on a per user basis (e.g. number of actions triggered, number of processes executed, number of interactions with other entities (requests/responses, notifications), etc.) along with a time indication (e.g. timespan, timestamp, etc.).
  • the NWDAF executes the corresponding analytics processes and derives the NF/NF service efficiency considering the information received in the previous steps.
  • the energy consumption information obtained in steps 212 and 213 is one input value
  • one or both of the computing resource usage information obtained in steps 214 and 215 and the number of allocated UEs obtained in steps 216 and 217 is another input value, from which the NF/NF service efficiency can be derived.
  • an efficiency measure can be calculated as the ratio of computing resource usage to energy consumption, or number of allocated UEs to energy consumption.
  • Using the number of UEs here is usually less accurate than using computing resource usage; however if computing resource usage information is not available, the number of allocated UEs can serve as an estimate therefore. This estimate is more accurate when the average activity level over all allocated UEs is constant, which may e.g. be the case when a high number of UEs is allocated to the NF.
  • efficiency information can be derived based on only one of the computing resource usage information and the number of allocated UEs, so the above steps of obtaining the respective other one thereof are expendable in this case.
  • Another option is to define a UE allocation efficiency, which can be expressed as the ratio of computing resource usage or energy consumption to the number of UEs.
  • the NWDAF sends to the NRF the energy efficiency for the NF in an analytic notify message, including the NF-ID, an indication of the efficiency analytics, for example as an Event-ID, and the energy efficiency.
  • the NWDAF's and MDAF's functionality can be combined in the same node.
  • Figure 3 is a signaling diagram illustrating a procedure for providing the energy efficiency of a network entity.
  • the procedure is performed by a network repository entity, an Operations Support System (OSS) 202, and the network entity.
  • the network data analytics entity is a NWDAF 115
  • the network repository entity is an NRF 110
  • the network entity is a NF 201.
  • the NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the NF sends a register request to the NRF.
  • the NF can include the energy efficiency in this message.
  • the NRF responds to the registration request.
  • the NF sends to the OSS a get energy consumption message to get the energy consumption information of the NF, including the NF-ID, optionally the timespan the NF is interested in, and also optionally the reporting information for the reports (e.g. desired periodicity, etc.).
  • the OSS sends to the NF an energy consumption report including the energy consumption of the NF, e.g. in terms of Jules, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
  • steps 313 and 314 are not performed, and the energy consumption information is obtained internally at the NF.
  • the NF sends to the OSS a get computing resources usage message to get the computing resources usage of the NF, including the NF-ID, optionally the timespan the NF is interested in, and also optionally the reporting information for the reports (e.g. desired periodicity, etc.).
  • the OSS sends to the NF a computing resources usage report including the computing resources usage of the NF, e.g. the computing load, the number of executed instructions, CPU cycles, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
  • a computing resources usage report including the computing resources usage of the NF, e.g. the computing load, the number of executed instructions, CPU cycles, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
  • steps 315 and 316 are not performed, and the computing resources usage information is obtained internally at the NF.
  • the NF derives the energy efficiency considering the information received in the previous messages or the information obtained internally at the NF.
  • the number of allocated UEs can be used to derive efficiency information in a similar manner as described with respect to Fig. 2, as the number of allocated UEs is usually known to the NF.
  • the NF sends to the NRF a NF update request including the energy efficiency.
  • the energy efficiency is included as part of the NF profile.
  • Figure 4 is a signaling diagram illustrating a procedure for discovering and selecting a NF/NF service based on energy efficiency objectives.
  • the procedure is performed by a network entity, a network repository entity and an Operations and Management (0AM) system 402.
  • the network entity is a consumer NF 401
  • the network repository entity is an NRF 110.
  • the 0AM system configures a NF selection policy in the NRF.
  • the NF selection policy includes energy efficiency objectives, for example energy consumption minimization.
  • the consumer NF sends to the NRF a discovery request including the NF type to discover.
  • the consumer NF may include an indication to minimize the energy consumption or discover the most efficient NF.
  • the NRF selects a NF based on the energy efficiency.
  • the NRF sends to the consumer NF a discovery response including the selected NF.
  • Figure 5 is a signaling diagram illustrating a procedure for discovering and selecting a NF/NF service based on energy efficiency objectives.
  • the procedure is performed by a network entity, a network repository entity and an Operations and Management (0AM) system 402.
  • the network entity is a consumer NF 401
  • the network repository entity is an NRF 110.
  • the 0AM system configures a NF selection policy in the consumer NF.
  • the NF selection policy includes energy efficiency objectives, for example energy consumption minimization.
  • the consumer NF sends to the NRF a discovery request including the NF type to discover.
  • the NRF sends to the consumer NF a discovery response including a set of discovered NFs/NF services.
  • the NRF includes the energy efficiency of said NF/NF service. In some example embodiments, the energy efficiency is included in the NFProfile/NFService.
  • the consumer NF selects the target NF based on the efficiency information provided by NRF.
  • Figure 6 is a flowchart illustrating a method performed by a network data analytics entity for providing the energy efficiency of a first network entity.
  • the network data analytics entity is a NWDAF 115.
  • the network data analytics entity receives from a third network entity a request for energy efficiency analytics of a first network entity.
  • the network data analytics entity transmits to the first network entity or a second network entity, a request to collect energy consumption information, computing resources usage information and/or information on the number of users of the first network entity.
  • the network data analytics entity receives from the first network entity or the second network entity, energy consumption information, computing resources usage information, and/or information on the number of users of the first network entity.
  • the network data analytics entity determines energy efficiency information of the first network entity.
  • the network data analytics entity transmits the determined energy efficiency of the first network entity to the third network entity.
  • Figure 7 is a flowchart illustrating a method performed by a network entity for providing the energy efficiency of said network entity.
  • the network entity is a NF or NF service.
  • the NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the network entity transmits to a second network entity, a request to collect energy consumption information of a first network entity and/or computing resources usage information of the first network entity.
  • the network entity receives from the second network entity the energy consumption information and/or the computing resources usage information of the first network entity.
  • the network entity determines energy efficiency information of the first network entity.
  • the network entity transmits the determined energy efficiency information of the first network entity to the third network entity.
  • Figure 8 is a flowchart illustrating a method performed by a network repository entity for discovering network entities based on energy efficiency.
  • the network repository entity is an NRF 110.
  • the network repository entity transmits to a network data analytics entity a request for energy efficiency analytics of a first network entity.
  • the network repository entity receives the energy efficiency of the first network entity.
  • the network repository entity receives from a second network entity a discovery request matching the first network entity.
  • the network repository entity performs the discovery of the first network entity.
  • the network repository entity transmits to the second network entity a discovery response including the network address of the first network entity including the energy efficiency.
  • Figure 9 is a flowchart illustrating a method performed by a network entity for discovering and selecting other network entities based on energy efficiency.
  • the network entity is a NF or NF service.
  • the NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the network entity transmits to a network repository entity a discovery request for a network entity of a certain type.
  • the network entity receives from the network repository entity a discovery response including a set of discovered network entities together with their energy efficiency information.
  • the network entity selects one of the network entities based on the energy efficiency information.
  • FIG 10 is a block diagram illustrating elements of a mobile network node 1000 of a mobile communications network.
  • the mobile network node 1000 is a NWDAF 115.
  • the mobile network node may include network interface circuitry 1001 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network.
  • the mobile network node may also include a processing circuitry 1002 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1003 (also referred to as memory) coupled to the processing circuitry.
  • the memory circuitry 1003 may include computer readable program code that when executed by the processing circuitry 1002 causes the processing circuitry to perform operations according to embodiments disclosed herein.
  • processing circuitry 1002 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1002 and/or network interface circuitry 1001. For example, processing circuitry 1002 may control network interface circuitry 1001 to transmit communications through network interface circuitry 1001 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1003, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1002, processing circuitry 1002 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
  • FIG 11 is a block diagram illustrating elements of a mobile network node 1100 of a mobile communications network.
  • the mobile network node 1100 is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the mobile network node may include network interface circuitry 1101 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network.
  • the mobile network node may also include a processing circuitry 1102 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1103 (also referred to as memory) coupled to the processing circuitry.
  • the memory circuitry 1103 may include computer readable program code that when executed by the processing circuitry 1102 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1102 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1102 and/or network interface circuitry 1101.
  • processing circuitry 1102 may control network interface circuitry 1101 to transmit communications through network interface circuitry 1101 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes.
  • modules may be stored in memory 1103, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1102, processing circuitry 1102 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
  • FIG. 12 is a block diagram illustrating elements of a mobile network node 1200 of a mobile communications network.
  • the mobile network node 1200 is an NRF 110.
  • the mobile network node may include network interface circuitry 1201 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network.
  • the mobile network node may also include a processing circuitry 1202 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1203 (also referred to as memory) coupled to the processing circuitry.
  • the memory circuitry 1203 may include computer readable program code that when executed by the processing circuitry 1202 causes the processing circuitry to perform operations according to embodiments disclosed herein.
  • processing circuitry 1202 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1202 and/or network interface circuitry 1201. For example, processing circuitry 1202 may control network interface circuitry 1201 to transmit communications through network interface circuitry 1201 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1203, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1202, processing circuitry 1202 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
  • FIG. 13 is a block diagram illustrating elements of a mobile network node 1300 of a mobile communications network.
  • the mobile network node 1300 is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
  • the mobile network node may include network interface circuitry 1301 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network.
  • the mobile network node may also include a processing circuitry 1302 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1303 (also referred to as memory) coupled to the processing circuitry.
  • the memory circuitry 1303 may include computer readable program code that when executed by the processing circuitry 1302 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1302 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1302 and/or network interface circuitry 1301.
  • processing circuitry 1302 may control network interface circuitry 1301 to transmit communications through network interface circuitry 1301 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes.
  • modules may be stored in memory 1303, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1302, processing circuitry 1302 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).

Abstract

A method for reducing the energy consumed by a mobile network by means of Network Function discovery and selection based on energy efficiency information. The method includes receiving energy efficiency information of a network entity at a network repository entity from a network data analytics entity and performing the discovery and selection of the network entity at the network repository entity based on the energy efficiency information. The energy efficiency information may be determined based on energy consumption information, computing resources usage information and/or the number of users of the network entity. The network data analytics entity may be a Network Data Analytics Function (NWDAF). The network repository entity may be a Network Repository Function (NRF). The network entity may be any Network Function or Network Function Service.

Description

ENERGY EFFICIENCY-BASED NETWORK FUNCTION DISCOVERY AND SELECTION
TECHNICAL FIELD
The present invention generally relates to the fields of energy efficiency, and more specifically, the invention relates to NF and NF service discovery and selection mechanisms to reduce the energy consumption in a mobile network.
BACKGROUND
The NWDAF (Network Data Analytics Function) provides analytics to 5GC (Fifth Generation Core) NFs (Network Functions) and OAM (Operations and Management) systems. Analytics information are either statistical information of past events, or predictive information. Different NWDAF instances may be present in the 5GC, with possible specializations per type of analytics. The capabilities of a NWDAF instance are described in the NWDAF profile stored in the NRF (Network Repository Function). Each NWDAF instance should provide the list of Analytics Identifiers (ID) that it supports when registering to the NRF, in addition to other NRF registration elements of the NF (Network Function) profile. Other NFs requiring the discovery of an NWDAF instance that provides support for some specific type of analytics may query the NRF and include the Analytics I D(s) that identifies the desired type of analytics for that purpose. The consumers, e.g. 5GC NFs and OAM, decide how to use the data analytics provided by NWDAF.
The Network Repository Function (NRF) is the entity in charge of Network Function (NF) and NF service discovery and selection. 3GPP TS 29.510 specifies that NF or NF service selection is based on information contained in the NFProfile resp. NFService data structures stored in NRF. In particular, the fields that are used for the NF or NF service selection decision are the priority, capacity and load. Priority is the priority relative to other NFs of the same type to be used for NF selection. Capacity is the static capacity information, which can be expressed as an absolute value or as a relative value with respect to the capacity of other NF instances of the same type. Load is dynamic load information that indicates the current load percentage of the NF. The load, capacity and priority parameters, if present, are used for NF selection and load balancing. Within the Operations and Support System (OSS), a Management Data Analytics Service (MDAS) provides data analytics of different network related parameters including for example load level and/or resource utilisation. For example, the MDAS for a network function (NF) can collect the NF's load related performance data, e.g. resource usage status of the NF. The analysis of the collected data may provide forecast of resource usage information in a predefined future time. This analysis may also recommend appropriate actions, e.g. scaling of resources, admission control, load balancing of traffic, etc. A MDAS for a network slice instance (NSI) provides NSI related data analytics. The service may consume the corresponding MDAS of its constituent NSSI(s). The NSI MDAS may further classify or shape the data in different useful categories according to different customer needs, e.g. slice load, constituent NSSI load, communication service loads. This data can be used for further analysis e.g. resource usage prediction, failure prediction for an NSI, etc.
Within the Operations and Support System (OSS), a Management Data Analytics Function (MDAF) provides the Management Data Analytics Service for one or more NF, NSSI and/or NSI, and may consume some management services produced by other functional blocks.
MDAS can be deployed at different levels, for example, at domain level (e.g. RAN, CN, NSSI) or in a centralized manner (e.g. in a PLMN level). A domain-level MDAS provides domain specific analytics, e.g. resource usage prediction in a CN or failure prediction in a NSSI, etc. A centralized MDAS can provide end-to-end or cross-domain analytics service, e.g. resource usage or failure prediction in an NSI, optimal CN node placement for ensuring lowest latency in the connected RAN, etc.
In an operator's network, for a same NF type, different implementations from different vendors (and different versions of the same vendor) coexist. This implies that to execute the same functionality, different NF implementations can consume a disparate amount of energy. This can be e.g. because some implementations are specifically optimized to reduce the amount of energy consumed, or because some implementations are faulty and consume an excessive amount of energy due to their bad software quality.
A problematic aspect is that current 3GPP solutions do not allow for NF or NF service discovery and selection aiming at selecting the NF resp. NF services that are more energy efficient, and thus minimizing the energy consumption in the operator's network. Current NF or NF service selection solutions are based on the priority, capacity and load information stored in NRF (NFProfile resp. NFService data structures). But none of these parameters give any information on the energy efficiency of the NFs or NF services to be selected.
A further problematic aspect is that current 3GPP specs do not provide any solution on how to obtain the energy efficiency of the different NF or NF service implementations.
SUMMARY
An object of the invention is to reduce the energy consumed by a mobile network.
A first aspect of the invention relates to a method performed by a network data analytics entity for providing energy efficiency information of a first network entity. The method includes receiving from the first network entity or a second network entity, energy consumption information of the first network entity; determining the energy efficiency information of the first network entity based on the energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity. In an embodiment of the method, the receiving step further comprises receiving computing resources usage information of the first network entity, and wherein the usage level information used in the determining step comprises the computing resources usage information of the first network entity. In an embodiment of the method, the receiving step further comprises receiving information on the number of users allocated to the first network entity, and wherein the usage level information used in the determining step comprises the number of users allocated to the first network entity. In an embodiment of the method, the method further comprises transmitting to the first network entity or the second network entity, a request to collect energy consumption information of the first network entity, computing resources usage information of the first network entity and/or information on the number of users allocated to the first network entity. In an embodiment of the method, the method further comprises receiving from the third network entity a request for energy efficiency information analytics of the first network entity. In an embodiment of the method, the first network entity is a Network Function, NF, or a NF service. In an embodiment of the method, the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. In an embodiment of the method, the third network entity is a network repository entity or a service discovery entity. A second aspect of the invention relates to a method performed by a first network entity for providing energy efficiency information of said first network entity. The method includes determining the energy efficiency information of the first network entity based on energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity. In an embodiment of the method, the method further includes receiving from a second network entity the energy consumption information and usage level information of the first network entity. In an embodiment of the method, the usage level information comprises computing resources usage information of the first network entity. In an embodiment of the method, the method further comprises receiving from the second network entity the computing resources usage information of the first network entity. In an embodiment of the method, the method further comprises transmitting to the second network entity, a request to collect energy consumption information of the first network entity and/or computing resources usage information of the first network entity. In an embodiment of the method, the first network entity is a Network Function, NF, or a NF service. In an embodiment of the method, the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. In an embodiment of the method, the third network entity is a network repository entity or a service discovery entity.
A third aspect of the invention relates to a method performed by a network repository entity for discovering network entities. The method includes receiving the energy efficiency information of a first network entity; receiving from a second network entity a discovery request matching the first network entity; performing the discovery and selection of the first network entity based on the energy efficiency information of the first network entity; and transmitting to the second network entity a discovery response including the network address of the first network entity. In an embodiment of the method, the method further includes transmitting to a network data analytics entity a request for energy efficiency information analytics of the first network entity, and wherein the energy efficiency information of the first network entity is received from said network data analytics entity. In an embodiment of the method, the energy efficiency information of the first network entity is received from the first network entity in a registration request or registration update message. In an embodiment of the method, the discovery of the first network entity is performed together with the discovery of other network entities matching the discovery request, and the discovery response further includes the network addresses of the other network entities, the energy efficiency information of the first network entity and the energy efficiency information of the other network entities. In an embodiment of the method, the first network entity is a Network Function, NF, or a NF service. In an embodiment of the method, the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. In an embodiment of the method, the third network entity is a network repository entity or a service discovery entity.
A fourth aspect of the invention relates to a method performed by a network entity for discovering and selecting other network entities based on energy efficiency information. The method includes transmitting to a network repository entity a discovery request for a network entity of a certain type; receiving from the network repository entity a discovery response including a set of discovered network entities together with their energy efficiency information; and selecting one of the network entities based on its energy efficiency information.
Other aspects of the invention relate to mobile network nodes, particularly a network data analytics entity, a network entity and a network repository entity, each configured to perform the respective methods as described herein.
In some embodiments of these aspects, the network data analytics entity is a Network Data Analytics Function (NWDAF) 115, the network repository entity is a Network Repository Function (NRF) 110 and the network entity is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
Advantageously, the solution disclosed herein enables mobile network operators to reduce the cost of the network operation by means of reducing the energy consumption of the mobile network.
Further advantageously, since the energy efficiency may depend not only on the NF implementation but also on the energy efficiency of the cloud infrastructure, the solution disclosed herein allows to select NFs deployed in more energy efficient cloud infrastructures, as the derived efficiency parameter includes the effects of both the NF's implementation and the cloud resources the NFs are deployed over.
Further advantageously, the solution disclosed herein enables environmental benefits, pollution reduction, etc.
Other objectives, features and advantages of the enclosed embodiments will be apparent from the following detailed disclosure, from the attached dependent claims as well as from the drawings.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the element, apparatus, component, means, module, step, etc." are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, module, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
BRIEF DESCRIPTION OF THE DRAWINGS
The invention may best be understood by referring to the following description and accompanying drawings that are used to illustrate particular embodiments of the invention. In the drawings:
Figure 1 is a networked system in accordance with particular embodiments of the solution described herein;
Figure 2 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
Figure 3 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
Figure 4 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein;
Figure 5 is a signaling diagram illustrating a procedure according to particular embodiments of the solution described herein; Figure 6 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
Figure 7 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
Figure 8 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
Figure 9 is a flowchart illustrating a method performed by a mobile network node according to particular embodiments of the solution described herein;
Figure 10 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
Figure 11 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
Figure 12 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
Figure 13 is a block diagram of a mobile network node configured in accordance with particular embodiments of the solution described herein.
DETAILED DESCRIPTION
The invention will now be described in detail hereinafter with reference to the accompanying drawings, in which examples of embodiments or implementations of the invention are shown. The invention may, however, be embodied or implemented in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present invention to those skilled in the art. It should also be noted that these embodiments are not mutually exclusive. Components from one embodiment may be tacitly assumed to be present/used in another embodiment. These embodiments of the disclosed subject matter are presented as teaching examples and are not to be construed as limiting the scope of the disclosed subject matter. For example, certain details of the described embodiments may be modified, omitted, or expanded upon without departing from the scope of the described subject matter. The example embodiments described herein arise in the context of a telecommunications network, including but not limited to a telecommunications network that conforms to and/or otherwise incorporates aspects of a fifth generation (5G) architecture.
Figure 1 is an example networked system 100 in accordance with example embodiments of the present disclosure. Figure 1 specifically illustrates User Equipment (UE) 101, which may be in communication with a (Radio) Access Network (RAN) 102 and Access and Mobility Management Function (AMF) 106 and User Plane Function (UPF) 103. The AMF 106 may, in turn, be in communication with core network services including Session Management Function (SMF) 107 and Policy Control Function (PCF) 111. The core network services may also be in communication with an Application Server/ Application Function (AS/AF) 113. Other networked services also include Network Slice Selection Function (NSSF) 108, Authentication Server Function (AUSF) 105, User Data Management (UDM) 112, Network Exposure Function (NEF) 109, Network Repository Function (NRF) 110, User Data Repository (UDR) 114, Network Data Analytics Function (NWDAF) 115 and Data Network (DN) 104. In some example implementations of embodiments of the present disclosure, an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108 are each considered to be an NF. One or more additional instances of these network functions (NF) may be incorporated into the networked system.
The solution described herein aims to reduce the energy consumed by a mobile network.
To achieve such object, this disclosure provides a method performed by a network data analytics entity, a network repository entity, and other network entities (specifically a first, a second and a third network entity). In some embodiments, the network data analytics entity is a NWDAF 115. In some embodiments, the network repository entity is an NRF 110. In some embodiments, the other network entities are NFs or NF services. The proposed solution applies to both NFs and NF services.
The method comprises receiving, at the network data analytics entity from the network repository entity, a request for energy efficiency information analytics of a first network entity; transmitting from the network data analytics entity to the first network entity or a second network entity, a request to collect energy consumption information of the first network entity, computing resource usage information of the first network entity and/or information on the number of users allocated to the first network entity; receiving, at the network data analytics entity from the first network entity or the second network entity, energy consumption information of the first network entity, computing resources usage information of the first network entity and/or the number of users allocated to the first network entity; determining, at the network data analytics entity, the energy efficiency information of the first network entity based on the energy consumption information of the first network entity, computing resource usage information of the first network entity and/or the number of users allocated to the first network entity; and transmitting from the network data analytics entity the determined energy efficiency information of the first network entity to a third network entity.
The method may also comprise determining, at the first network entity, the energy efficiency information of the first network entity based on energy consumption information of the first network entity, computing resources usage information of the first network entity and/or the number of users allocated to the first network entity; and transmitting from the first network entity the determined energy efficiency information of the first network entity to the network repository entity.
The method further comprises receiving at the network repository entity the energy efficiency information of a first network entity; receiving at the network repository entity from a second network entity a discovery request matching the first network entity; performing at the network repository entity the discovery and selection of the first network entity based on the energy efficiency information of the first network entity; and transmitting from the network repository entity to the second network entity a discovery response including the network address of the first network entity.
In some embodiments of the method, the first network entity is a Network Function, NF, or a NF service. In some embodiments of the method, the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF 113, or an energy consumption monitoring system. In some embodiments of the method, the third network entity is a network repository entity or a service discovery entity, more specifically an NRF 110. The NF can be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108. In some example embodiments, the method comprises including a new parameter in the NFProfile/NFService in NRF 110, so called "efficiency", denoting how efficient in terms of energy consumption is the corresponding NF or NF service. This parameter can be specified in relative terms among NFs/NF services (as the priority or capacity parameters are currently specified) or as an absolute value (e.g. in terms of energy consumed per user, or energy consumed per executed computing instruction, etc.)
In some example embodiments, the method comprises deriving the "efficiency" using the analytics capabilities of the Core Network (NWDAF) and OSS (MDAF). For example, to derive the efficiency, NWDAF may collect the following information on a per NF/NF service basis over a certain timespan:
• Number of active users allocated to the NF/NF service
• Activity level - Indicative of the level of activity of the NF/NF service, e.g. number of actions triggered, number of processes executed, number of interactions with other entities (requests/responses, notifications), etc.
• Absolute computing load - e.g. number of executed instructions, etc.
• Energy consumption - e.g. in terms of Jules, etc.
NWDAF may also collect the absolute computing load and energy consumption from other entities within OSS, for example the absolute computing load from the orchestrator and the energy consumption from an energy monitoring entity measuring the amount of electric energy consumed by the cloud resources (e.g. NFs). This entity may aggregate all energy used in a data center (e.g. servers, cooling, etc.) and extract statistics on the energy consumed per cloud resource.
In some example embodiments, the NRF 110 can request/subscribe to the efficiency analytics in NWDAF for a concrete NF/NF service.
In some example embodiments, a consumer NF/NF service can discover NFs/NF services based on energy efficiency optimization objectives, for example by sending an indication to NRF to retrieve the most energy efficient NFs/NF services, or by receiving the efficiency values in the NFProfile/NFService and selecting the most efficient ones locally in the consumer NF/NF service. The definition of the NFProfile (and NFService) data structures in NRF may be extended as follows:
Figure imgf000013_0001
Figure imgf000014_0001
This disclosure also provides mobile network nodes, particularly a network data analytics entity 1000, a network entity 1100, and a network repository entity 1200 and a further network entity 1300, each configured to perform the respective methods as described herein. In some embodiments the network data analytics entity 1000 is a NWDAF 115, the network repository entity 1200 is an NRF 110, and the network entities 1100 and 1300 are any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
Advantageously, the solution disclosed herein enables mobile network operators to reduce the cost of the network operation by means of reducing the energy consumption of the mobile network.
Further advantageously, since the energy efficiency may depend not only on the NF implementation but also on the energy efficiency of the cloud infrastructure, the solution disclosed herein allows to select NFs deployed in more energy efficient cloud infrastructures, as the derived efficiency parameter includes the effects of both the NF's implementation and the cloud resources the NFs are deployed over.
Further advantageously, the solution disclosed herein enables environmental benefits, pollution reduction, etc.
Hereinafter, drawings showing examples of embodiments of the solution are described in detail.
Figure 2 is a signaling diagram illustrating a procedure for providing the energy efficiency of a network entity. The procedure is performed by a network data analytics entity, a network repository entity, an Operations Support System (OSS) 202, and the network entity. In this figure, the network data analytics entity is a NWDAF 115, the network repository entity is an NRF 110, and the network entity is a NF 201. The NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
At step 211, the NRF subscribes to NWDAF for energy efficiency analytics of a NF, including an indication of the efficiency analytics, for example as an Event-ID, and the NF-ID.
At step 212, the NWDAF sends to the OSS a request to get energy consumption information of the NF, including the NF-ID. Optionally, the message may include the timespan the NWDAF is interested in, and the reporting information for the reports (e.g. desired periodicity, etc.).
In some example embodiments, the OSS is a Cloud Orchestrator, a management data analytics entity (for example an MDAF), an Application Function (AF 113) or an energy consumption monitoring system.
At step 213, the OSS sends to the NWDAF an energy consumption report for the NF including the NF-ID, the energy consumption, e.g. in terms of Jules, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
At step 214, NWDAF sends to the OSS a request or subscription request for computing resources usage information of a NF, including the NF-ID. Optionally, the message may include the timespan the NWDAF is interested in, and the reporting information for the reports (e.g. desired periodicity, etc.).
At step 215, the OSS sends to the NWDAF a computing resources usage information report including the NF-ID, the computing resources usage information, e.g. number of executed instructions, CPU cycles, etc., and optionally, a timespan or timestamp pertaining to the computing resources usage information.
At step 216, the NWDAF may get the number of UEs allocated to the NF by sending a request to the NF. In some example embodiments, this step can be done via standard mechanisms, e.g. querying UDR for the users allocated to SMF or AMF, querying SMF for the users allocated to UPF, etc.
At step 217, the NWDAF receives the information on the number of users allocated to the NF. In some example embodiments, this message may also include the activity level on a per user basis (e.g. number of actions triggered, number of processes executed, number of interactions with other entities (requests/responses, notifications), etc.) along with a time indication (e.g. timespan, timestamp, etc.).
At step 218, the NWDAF executes the corresponding analytics processes and derives the NF/NF service efficiency considering the information received in the previous steps.
Particularly, the energy consumption information obtained in steps 212 and 213 is one input value, and one or both of the computing resource usage information obtained in steps 214 and 215 and the number of allocated UEs obtained in steps 216 and 217 is another input value, from which the NF/NF service efficiency can be derived.
For example, an efficiency measure can be calculated as the ratio of computing resource usage to energy consumption, or number of allocated UEs to energy consumption. Using the number of UEs here is usually less accurate than using computing resource usage; however if computing resource usage information is not available, the number of allocated UEs can serve as an estimate therefore. This estimate is more accurate when the average activity level over all allocated UEs is constant, which may e.g. be the case when a high number of UEs is allocated to the NF.
As can be seen, efficiency information can be derived based on only one of the computing resource usage information and the number of allocated UEs, so the above steps of obtaining the respective other one thereof are expendable in this case.
Another option is to define a UE allocation efficiency, which can be expressed as the ratio of computing resource usage or energy consumption to the number of UEs.
At step 219, the NWDAF sends to the NRF the energy efficiency for the NF in an analytic notify message, including the NF-ID, an indication of the efficiency analytics, for example as an Event-ID, and the energy efficiency.
In some example embodiments, the NWDAF's and MDAF's functionality can be combined in the same node.
Figure 3 is a signaling diagram illustrating a procedure for providing the energy efficiency of a network entity. The procedure is performed by a network repository entity, an Operations Support System (OSS) 202, and the network entity. In this figure, the network data analytics entity is a NWDAF 115, the network repository entity is an NRF 110, and the network entity is a NF 201. The NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
At step 311, the NF sends a register request to the NRF. In some example embodiments, if the NF already knows the energy efficiency, the NF can include the energy efficiency in this message.
At step 312, the NRF responds to the registration request.
At step 313, the NF sends to the OSS a get energy consumption message to get the energy consumption information of the NF, including the NF-ID, optionally the timespan the NF is interested in, and also optionally the reporting information for the reports (e.g. desired periodicity, etc.).
At step 314, the OSS sends to the NF an energy consumption report including the energy consumption of the NF, e.g. in terms of Jules, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
In some example embodiments, steps 313 and 314 are not performed, and the energy consumption information is obtained internally at the NF.
At step 315, the NF sends to the OSS a get computing resources usage message to get the computing resources usage of the NF, including the NF-ID, optionally the timespan the NF is interested in, and also optionally the reporting information for the reports (e.g. desired periodicity, etc.).
At step 316, the OSS sends to the NF a computing resources usage report including the computing resources usage of the NF, e.g. the computing load, the number of executed instructions, CPU cycles, etc., and optionally, a timespan or timestamp pertaining to the energy consumption.
In some example embodiments steps 315 and 316 are not performed, and the computing resources usage information is obtained internally at the NF.
At step 317, the NF derives the energy efficiency considering the information received in the previous messages or the information obtained internally at the NF. Of course, also in this example the number of allocated UEs can be used to derive efficiency information in a similar manner as described with respect to Fig. 2, as the number of allocated UEs is usually known to the NF.
At step 318, the NF sends to the NRF a NF update request including the energy efficiency. In some example embodiments, the energy efficiency is included as part of the NF profile.
Figure 4 is a signaling diagram illustrating a procedure for discovering and selecting a NF/NF service based on energy efficiency objectives. The procedure is performed by a network entity, a network repository entity and an Operations and Management (0AM) system 402. In this figure, the network entity is a consumer NF 401, and the network repository entity is an NRF 110.
At step 411, the 0AM system configures a NF selection policy in the NRF. In some example embodiments, the NF selection policy includes energy efficiency objectives, for example energy consumption minimization.
At step 412, the consumer NF sends to the NRF a discovery request including the NF type to discover. In some example embodiments, the consumer NF may include an indication to minimize the energy consumption or discover the most efficient NF.
At step 413, the NRF selects a NF based on the energy efficiency.
At step 414, the NRF sends to the consumer NF a discovery response including the selected NF.
Figure 5 is a signaling diagram illustrating a procedure for discovering and selecting a NF/NF service based on energy efficiency objectives. The procedure is performed by a network entity, a network repository entity and an Operations and Management (0AM) system 402. In this figure, the network entity is a consumer NF 401, and the network repository entity is an NRF 110.
At step 511, the 0AM system configures a NF selection policy in the consumer NF. In some example embodiments, the NF selection policy includes energy efficiency objectives, for example energy consumption minimization.
At step 512, the consumer NF sends to the NRF a discovery request including the NF type to discover. At step 513, the NRF sends to the consumer NF a discovery response including a set of discovered NFs/NF services. For each discovered NF/NF service, the NRF includes the energy efficiency of said NF/NF service. In some example embodiments, the energy efficiency is included in the NFProfile/NFService.
At step 514, the consumer NF selects the target NF based on the efficiency information provided by NRF.
Figure 6 is a flowchart illustrating a method performed by a network data analytics entity for providing the energy efficiency of a first network entity. In some embodiments, the network data analytics entity is a NWDAF 115.
At step 601, the network data analytics entity receives from a third network entity a request for energy efficiency analytics of a first network entity.
At step 602, the network data analytics entity transmits to the first network entity or a second network entity, a request to collect energy consumption information, computing resources usage information and/or information on the number of users of the first network entity.
At step 603, the network data analytics entity receives from the first network entity or the second network entity, energy consumption information, computing resources usage information, and/or information on the number of users of the first network entity.
At step 604, the network data analytics entity determines energy efficiency information of the first network entity.
At step 605, the network data analytics entity transmits the determined energy efficiency of the first network entity to the third network entity.
Figure 7 is a flowchart illustrating a method performed by a network entity for providing the energy efficiency of said network entity. In some example embodiments, the network entity is a NF or NF service. The NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
At step 701, the network entity transmits to a second network entity, a request to collect energy consumption information of a first network entity and/or computing resources usage information of the first network entity. At step 702, the network entity receives from the second network entity the energy consumption information and/or the computing resources usage information of the first network entity.
At step 703, the network entity determines energy efficiency information of the first network entity.
At step 704, the network entity transmits the determined energy efficiency information of the first network entity to the third network entity.
Figure 8 is a flowchart illustrating a method performed by a network repository entity for discovering network entities based on energy efficiency. In some embodiments, the network repository entity is an NRF 110.
At step 801, the network repository entity transmits to a network data analytics entity a request for energy efficiency analytics of a first network entity.
At step 802, the network repository entity receives the energy efficiency of the first network entity.
At step 803, the network repository entity receives from a second network entity a discovery request matching the first network entity.
At step 804, the network repository entity performs the discovery of the first network entity.
At step 805, the network repository entity transmits to the second network entity a discovery response including the network address of the first network entity including the energy efficiency.
Figure 9 is a flowchart illustrating a method performed by a network entity for discovering and selecting other network entities based on energy efficiency. In some example embodiments, the network entity is a NF or NF service. The NF may be any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108.
At step 901, the network entity transmits to a network repository entity a discovery request for a network entity of a certain type. At step 902, the network entity receives from the network repository entity a discovery response including a set of discovered network entities together with their energy efficiency information.
At step 903, the network entity selects one of the network entities based on the energy efficiency information.
Figure 10 is a block diagram illustrating elements of a mobile network node 1000 of a mobile communications network. In some embodiments, the mobile network node 1000 is a NWDAF 115. As shown, the mobile network node may include network interface circuitry 1001 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network. The mobile network node may also include a processing circuitry 1002 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1003 (also referred to as memory) coupled to the processing circuitry. The memory circuitry 1003 may include computer readable program code that when executed by the processing circuitry 1002 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1002 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1002 and/or network interface circuitry 1001. For example, processing circuitry 1002 may control network interface circuitry 1001 to transmit communications through network interface circuitry 1001 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1003, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1002, processing circuitry 1002 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
Figure 11 is a block diagram illustrating elements of a mobile network node 1100 of a mobile communications network. In some embodiments, the mobile network node 1100 is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108. As shown, the mobile network node may include network interface circuitry 1101 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network. The mobile network node may also include a processing circuitry 1102 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1103 (also referred to as memory) coupled to the processing circuitry. The memory circuitry 1103 may include computer readable program code that when executed by the processing circuitry 1102 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1102 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1102 and/or network interface circuitry 1101. For example, processing circuitry 1102 may control network interface circuitry 1101 to transmit communications through network interface circuitry 1101 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1103, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1102, processing circuitry 1102 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
Figure 12 is a block diagram illustrating elements of a mobile network node 1200 of a mobile communications network. In some embodiments, the mobile network node 1200 is an NRF 110. As shown, the mobile network node may include network interface circuitry 1201 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network. The mobile network node may also include a processing circuitry 1202 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1203 (also referred to as memory) coupled to the processing circuitry. The memory circuitry 1203 may include computer readable program code that when executed by the processing circuitry 1202 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1202 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1202 and/or network interface circuitry 1201. For example, processing circuitry 1202 may control network interface circuitry 1201 to transmit communications through network interface circuitry 1201 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1203, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1202, processing circuitry 1202 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).
Figure 13 is a block diagram illustrating elements of a mobile network node 1300 of a mobile communications network. In some embodiments, the mobile network node 1300 is any one of an AMF 106, SMF 107, UPF 103, PCF 111, AUSF 105, NRF 110, UDM 112, NEF 109, AF 113, UDR 114, NWDAF 115, and NSSF 108. As shown, the mobile network node may include network interface circuitry 1301 (also referred to as a network interface) configured to provide communications with other nodes of the core network and/or the network. The mobile network node may also include a processing circuitry 1302 (also referred to as a processor) coupled to the network interface circuitry, and memory circuitry 1303 (also referred to as memory) coupled to the processing circuitry. The memory circuitry 1303 may include computer readable program code that when executed by the processing circuitry 1302 causes the processing circuitry to perform operations according to embodiments disclosed herein. According to other embodiments, processing circuitry 1302 may be defined to include memory so that a separate memory circuitry is not required. As discussed herein, operations of the mobile network node may be performed by processing circuitry 1302 and/or network interface circuitry 1301. For example, processing circuitry 1302 may control network interface circuitry 1301 to transmit communications through network interface circuitry 1301 to one or more other network nodes and/or to receive communications through network interface circuitry from one or more other network nodes. Moreover, modules may be stored in memory 1303, and these modules may provide instructions so that when instructions of a module are executed by processing circuitry 1302, processing circuitry 1302 performs respective operations (e.g., operations discussed below with respect to Example Embodiments relating to core network nodes).

Claims

- 22 -
CLAIMS A method performed by a network data analytics entity for providing energy efficiency information of a first network entity, the method comprising: receiving from the first network entity or a second network entity, energy consumption information of the first network entity; determining the energy efficiency information of the first network entity based on the energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity. The method of claim 1, wherein the receiving step further comprises receiving computing resources usage information of the first network entity, and wherein the usage level information used in the determining step comprises the computing resources usage information of the first network entity. The method of claim 1, wherein the receiving step further comprises receiving information on the number of users allocated to the first network entity, and wherein the usage level information used in the determining step comprises the number of users allocated to the first network entity. The method of any one of claims 1 to 3, further comprising: transmitting to the first network entity or the second network entity, a request to collect energy consumption information of the first network entity, computing resources usage information of the first network entity and/or information on the number of users allocated to the first network entity. The method of any one of claims 1 to 4, further comprising: receiving from the third network entity a request for energy efficiency information analytics of the first network entity. The method of any one of claims 1 to 5, wherein the first network entity is a Network Function, NF, or a NF service. The method of any one of claims 1 to 5, wherein the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. The method of any one of claims 1 to 5, wherein the third network entity is a network repository entity or a service discovery entity. A method performed by a first network entity for providing energy efficiency information of said first network entity, the method comprising: determining the energy efficiency information of the first network entity based on energy consumption information and usage level information of the first network entity; and transmitting the determined energy efficiency information of the first network entity to a third network entity. The method of claim 9, further comprising: receiving from a second network entity the energy consumption information and usage level information of the first network entity. The method of any of claims 9 to 10, wherein the usage level information comprises computing resources usage information of the first network entity. The method of claim 11, further comprising: receiving from the second network entity the computing resources usage information of the first network entity. The method of any one of claims 9 to 12, further comprising: transmitting to the second network entity, a request to collect energy consumption information of the first network entity and/or computing resources usage information of the first network entity. The method of any one of claims 9 to 13, wherein the first network entity is a Network Function, NF, or a NF service. The method of any one of claims 9 to 13, wherein the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. The method of any one of claims 9 to 13, wherein the third network entity is a network repository entity or a service discovery entity. A method performed by a network repository entity for discovering network entities, the method comprising: receiving the energy efficiency information of a first network entity; receiving from a second network entity a discovery request matching the first network entity; performing the discovery and selection of the first network entity based on the energy efficiency information of the first network entity; and transmitting to the second network entity a discovery response including the network address of the first network entity. The method of claim 17, further comprising transmitting to a network data analytics entity a request for energy efficiency information analytics of the first network entity, and wherein the energy efficiency information of the first network entity is received from said network data analytics entity. The method of claim 17, wherein the energy efficiency information of the first network entity is received from the first network entity in a registration request or registration update message. - 25 - The method of any one of claims 17 to 19, wherein the discovery of the first network entity is performed together with the discovery of other network entities matching the discovery request, and the discovery response further includes the network addresses of the other network entities, the energy efficiency information of the first network entity and the energy efficiency information of the other network entities. The method of any one of claims 17 to 20, wherein the first network entity is a Network Function, NF, or a NF service. The method of any one of claims 17 to 20, wherein the second network entity is a Network Function, NF, a NF service, an Operations Support System, OSS, a Cloud Orchestrator, a management data analytics entity, an Application Function, AF, or an energy consumption monitoring system. The method of any one of claims 17 to 20, wherein the third network entity is a network repository entity or a service discovery entity. A method performed by a network entity for discovering and selecting other network entities based on energy efficiency information, the method comprising: transmitting to a network repository entity a discovery request for a network entity of a certain type; receiving from the network repository entity a discovery response including a set of discovered network entities together with their energy efficiency information; and selecting one of the network entities based on its energy efficiency information. A network data analytics entity configured to perform the method of any one of claims 1 to 8. The network data analytics entity of claim 25, comprising processing circuitry and a non-transitory machine-readable medium storing instructions which, when executed by the processing circuitry, cause the network data analytics entity to perform the method of any one of claims 1 to 8. - 26 - A network entity configured to perform the method of any one of claims 9 to 16. The network entity of claim 27 comprising processing circuitry and a non-transitory machine-readable medium storing instructions which, when executed by the processing circuitry, cause the network data analytics entity to perform the method of any one of claims 9 to 16. A network repository entity configured to perform the method of any one of claims 17 to 23. The network repository of claim 29, comprising processing circuitry and a non- transitory machine-readable medium storing instructions which, when executed by the processing circuitry, cause the network data analytics entity to perform the method of any one of claims 17 to 23. A network entity configured to perform the method of claim 24. The network entity of claim 31, comprising processing circuitry and a non-transitory machine-readable medium storing instructions which, when executed by the processing circuitry, cause the network data analytics entity to perform the method of any one of claim 24. A system comprising a network data analytics entity according to any one of claims from 25 to 26, a network entity according to any one of claims from 27 to 28, a network repository entity according to any one of claims from 29 to 30, and a network entity according to any one of claims from 31 to 32.
PCT/EP2021/054331 2020-09-15 2021-02-22 Energy efficiency-based network function discovery and selection WO2022058049A1 (en)

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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3179673A1 (en) * 2014-08-25 2017-06-14 Huawei Technologies Co. Ltd. Energy-saving control method, management server and network device

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Publication number Priority date Publication date Assignee Title
EP3179673A1 (en) * 2014-08-25 2017-06-14 Huawei Technologies Co. Ltd. Energy-saving control method, management server and network device

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"3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Study on enablers for network automation for the 5G System (5GS); Phase 2 (Release 17)", no. V0.4.0, 1 July 2020 (2020-07-01), pages 1 - 186, XP051925862, Retrieved from the Internet <URL:ftp://ftp.3gpp.org/Specs/archive/23_series/23.700-91/23700-91-040.zip 23700-91-040_rm_r06.doc> [retrieved on 20200701] *

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