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6.1.1.2 Information Flows
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6.1.1.2.1 General
The following information flows are specified for energy saving candidate entity.
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6.1.1.2.2 Energy saving candidate entity request
Table 6.1.1.2.2-1 shows the request sent by a SEAL service consumer to a SEAL server for energy saving candidate entity procedure. Table 6.1.1.2.2-1: Energy saving candidate entity request Information element Status Description Requestor identifier M The identifier of the requestor. VAL service ID M The ide...
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6.1.1.2.3 Energy saving candidate entity response
Table 6.1.1.2.3-1 shows the response sent by the ESE server to the consumer for energy saving candidate entity procedure. Table 6.1.1.2.3-1: Energy saving candidate entity response Information element Status Description Result M The result of the request (positive or negative acknowledgement). Subscription ID ...
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6.1.1.2.4 Energy saving candidate entity notify
Table 6.1.1.2.4-1 shows the notification sent by the ESE server to the consumer for energy saving candidate entity procedure. Table 6.1.1.2.4-1: Energy saving candidate entity notify Information element Status Description Success status O (NOTE) Indicates that energy saving assistance was successful. > candida...
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6.1.2 Architecture impacts
A new ESE server service is introduced with the corresponding service API: - ESE Energy Saving candidate entity API (subscribe / notify model; API provider: ESE server; known consumer: VAL server, SEAL server/client; corresponding to steps 1, 3, and 7 of clause 6.1.1.1).
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6.1.3 Solution evaluation
This solution addresses KI #1 on enhance functional architecture to support energy saving by introducing a new common service on energy saving candidate entity. The ESE server provides information which can be used by consumer to make decision/adjustment on entity selection for save energy on its application operations...
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6.2.1 Solution Description
The proposed solution solves the problem listed in KI #1 and KI #3 and proposes to consider Renewable energy in edge computing. In Edge Computing deployment, an application service may be served by multiple Edge Application Servers typically deployed in different sites. These multiple Edge Application Servers that hos...
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6.2.2 Architecture impacts
In this solution, it doesn’t change the overall architecture of enabling edge applications defined in section 6.2 of 3GPP TS 23.558 [8]. But the following enhancements are added: - The EES can subscribe to EAS whether renewable is consumed by EAS. If the EAS consumes the renewable energy, for example in the morning ti...
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6.2.3 Procedure
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6.2.3.1 Procedure of subscription Energy information from EAS
Figure 6.2.3.1-1: EAS energy information subscription 1. The EES sends an EAS energy information subscription request to the EAS. The EAS energy information subscription request includes the EES ID along with the security credentials, Event ID and time period to subscribe to information about energy information of E...
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6.2.3.2 Procedure of EAS discovery considering renewable energy information
The procedure listed here are based on the procedure defined in section 8.5.2.2 of 3GPP TS 23.558 [8].
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8.5.2.2 Request-response model
Pre-conditions: 1. The EEC has received information (e.g. URI, IP address) related to the EES; 2. The EEC has received appropriate security credentials authorizing it to communicate with the EES as specified in clause 8.11; and 3. The EES is configured with ECSP's policy for EAS discovery. NOTE 1: Details of ECSP's...
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6.2.4 Solution evaluation
This solution addresses Key Issue #1 – open issue #1 on how to enhance application enablement layer architecture and services to support energy saving, and Key Issue #3 – open issue #1 on how to enhance EDGE application enablement layer to support energy saving and energy efficiency. The solution proposes enhancements ...
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6.3.1 Solution Description
According to the key issue #3, there is a need for EDGE application enablement layer enhance to support energy saving. The services procedures and information flows introduced in 3GPP TS 23.558 [8] for edge services, can be enhanced to support the energy saving requirements. The procedure for EAS discovery as specifie...
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8.5.3.2 EAS discovery request
Table 8.5.3.2-1 describes information elements for the EAS discovery request. Table 8.5.3.2-2 provides further detail about the EAS Discovery Filter information element. Table 8.5.3.2-1: EAS discovery request Information element Status Description Requestor identifier M The ID of the requestor (e.g. EECID) UE I...
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8.2.4 EAS Profile
An EAS Profile includes information about an EAS used to describe services and service characteristics offered. NOTE 1: Information elements in the EAS Profile are provided by the ASP. Table 8.2.4-1: EAS Profile Information element Status Description EASID M The identifier of the EAS EAS Endpoint M Endpoin...
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6.3.2 Architecture impacts
No architecture impact has been identified.
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6.3.3 Solution evaluation
This solution addresses the open issue #2 in Key Issue #3, on how EDGE application enablement service could be enhanced to support energy saving and energy efficiency. The EES service on EAS discovery, the EAS Profile for EAS registration and discovery are enhanced by adding energy type IE. The energy type IE indicates...
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6.4.1 Solution Description
This solution addresses Key Issue #4 – open issue #3 on how to use energy consumption information for AIMLE client selection. The solution proposes enhancements to the ML model information management procedure, and to procedures involving AIMLE client selection, to enable the storage and use of energy consumption infor...
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6.4.1.1 Impact to ML model information management
The ML model information management procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.11.4.1 ML model information storage request
Table 8.11.4.1-1 describes the information flow from the AIMLE server to the ML repository or from the AIMLE client/VAL server to the AIMLE server as a request for the ML model information storage. Table 8.11.4.1-1: ML model information storage request Information element Status Description Requestor Identity M ...
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6.4.1.2 Impact to AIMLE client registration
The AIMLE client registration procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.7.2.2 AIMLE client registration
Pre-conditions: 1. The AIMLE client has been pre-configured or has discovered the address (e.g., URI) of the AIMLE server. 2. The AIMLE client has been pre-configured with an AIMLE client profile. Figure 8.7.2.2-1: AIMLE client registration 1. The AIMLE client sends an AIMLE client registration request to the...
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8.7.3.2 AIMLE client registration request
Table 8.7.3.2-1 shows the request sent by an AIMLE client to an AIMLE server for the AIMLE client registration request. Table 8.7.3.2-1: AIMLE client registration request Information element Status Description Requestor identifier M The identifier of the requestor. List of supported profiles M Supported AIML ...
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6.4.1.3 Impact to AIMLE client discovery
The AIMLE client selection procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.8.3.1 AIMLE client discovery request
Table 8.8.3.1-1 shows the request sent by a VAL server to an AIMLE server for the AIMLE client discovery procedure. Table 8.8.3.1-1: AIMLE client discovery request Information element Status Description Requestor identity M The identifier of the requestor (e.g., VAL server). AIMLE client discovery criteria M ...
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6.4.1.4 Impact to AIMLE client selection
The AIMLE client selection procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.9.2.1 AIMLE client selection
Pre-conditions: 1. AIMLE clients that support AI/ML operations have registered with the AIMLE server and included their AIMLE client profiles and optionally a list of supported services. 2. The AIMLE server can access a ML repository to obtain AIMLE client profiles and supported services associated with the AIMLE cli...
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6.4.1.5 Impact to AIMLE client selection subscription
The AIMLE client selection subscription procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.13.2.2 AIMLE client selection subscription and notification
Figure 8.13.2.2-1: AIMLE client selection subscription and notification 1. A VAL server sends an AIMLE client selection subscription request to the AIMLE Server. The AIMLE client selection subscription request includes information as described in Table 8.13.3-1 which includes selection criteria. 2. The AIMLE server...
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6.4.1.6 Impact to AIMLE client participation
The AIMLE client participation procedure and information flows in 3GPP TS 23.482 [10] are enhanced (highlighted in bold italics) as follows.
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8.10.3.1 AIMLE client participation request
Table 8.10.3.1-1 shows the request sent by the AIMLE server to each AIMLE client selected for AIMLE client participation procedure. Table 8.10.3.1-1: AIMLE client participation request Information element Status Description Requestor identity M The identifier of the requestor. AIMLE client set identifier M An...
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6.4.2 Architecture impacts
None.
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6.4.3 Solution evaluation
This solution addresses Key Issue #4 – open issue #3 on how to use energy consumption information for AIMLE client selection. The solution proposes enhancements to 3GPP TS 23.482 [10] to enable the storage and use of energy consumption information for AIMLE client selection. The solution enhances the ML model informat...
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6.5.1 Solution Description
The proposed solution solves the problem listed in KI #1 and KI #4, and proposes to consider renewable energy in AIMLE. As indicated in 3GPP TS 28.310 [4], the renewable energy and renewable energy factor have the following definitions: Renewable energy: energy from renewable non-fossil sources. NOTE 15: This defini...
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6.5.2 Architecture impacts
In this solution, it doesn’t change the overall architecture of Application enablement architecture of AIMLE in section 5 of 3GPP TS 23.482 [10]. But the following enhancements are added: - The FL member can register itself of the new capability that support renewable energy supply. - The subscriber can be notified w...
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6.5.3 Procedure
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6.5.3.1 Procedure of FL member registration procedure
This procedure is the same as the procedure in section 8.4.2 of 3GPP TS 23.482 [10] with the following enhancement:
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8.4.2 Procedure on FL member registration
Figure 8.4.2-1 illustrates the procedure where the registration of a candidate FL member happens via the ML repository, serving as AIML service registry. Figure 8.4.2-1: Procedure for registration on FL member registry 1. The candidate FL member (e.g., VAL server via AIMLE server or AIMLE server) sends an FL m...
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6.5.3.2 Procedure of FL-related event subscription of renewable energy
This procedure is the same as the procedure in section 8.5.2 of 3GPP TS 23.482 [10] with the following enhancement:
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8.5.2 Procedure on subscription for FL related events
This procedure, as illustrated in Figure 8.5.2-1, describes the subscription for events related to FL member availability. Pre-conditions: 1. The AIMLE server has the authorization to subscribe for the FL-related events (events described in clause 8.5.4). Figure 8.5.2-1: Procedure for FL-related event subscriptio...
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6.5.3.3 Procedure of member selection during ML model training considering renewable energy
This procedure is the same as the procedure in section 8.3.2 of 3GPP TS 23.482 [10] with the following enhancement:
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8.3.2 Procedure for ML model training
Figure 8.3.2-1 illustrates the procedure for AIMLE server to support ML model training based on the request from the VAL server. Figure 8.3.2-1: ML model training 1. The VAL server sends an ML model training request to AIMLE server, requesting to assist in its ML model training. This request consists of ML model in...
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6.5.4 Solution evaluation
This solution addresses Key Issue #1 – open issue #1 on how to enhance application enablement layer architecture and services to support energy saving, Key Issue #4 – open issue #2 on enhance AIMLE to support for energy saving, and Key Issue #4 – open issue #3 on FL member selection with energy consumption information....
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6.6.1 Solution Description
This solution addresses Key Issue #4 – open issue #1 on how to collect and use energy consumption data. The solution proposes a new ADAE service procedure in 3GPP TS 23.436 [11] to support AI/ML energy consumption analytics.
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6.6.1.1 Procedure
Figure 6.6.1.1-1 illustrates the procedure for a consumer (e.g., VAL server, AIMLE server) to subscribe for AI/ML energy consumption analytics generated from data collected from VAL UEs while the VAL UEs are performing AI/ML operations. Pre-conditions: 1. ADAE Client (ADAEC) is connected to the ADAE Server (ADAES). ...
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6.6.1.2 Information flows
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6.6.1.2.1 AI/ML energy consumption analytics subscription request
Table 6.6.1.2.1-1 describes the information flow from the consumer (e.g. VAL server, AIMLE server) as a request or update request for AI/ML energy consumption analytics. Table 6.6.1.2.1-1: AI/ML energy consumption analytics subscription request Information element Status Description Requestor ID M The identifier...
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6.6.1.2.2 AI/ML energy consumption analytics subscription response
Table 6.6.1.2.2-1 describes the information elements for the AI/ML energy consumption analytics subscription response from the ADAES to the consumer. Table 6.6.1.2.2-1: AI/ML energy consumption analytics subscription response Information element Status Description Result M The result of the analytics subscriptio...
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6.6.1.2.3 AI/ML energy consumption analytics notification
Table 6.6.1.2.3-1 describes the information flow from the ADAES to the consumer (e.g. VAL Server, AIMLE Server) as a notification for the AI/ML energy consumption analytics. Table 6.6.1.2.3-1: AI/ML energy consumption analytics notification Information element Status Description Subscription ID M The identifier ...
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6.6.1.2.4 AI/ML energy consumption data collection subscription request
Table 6.6.1.2.4-1 describes information elements for the AI/ML energy consumption data collection subscription request from the ADAES to the ADAEC. Table 6.6.1.2.4-1: AI/ML energy consumption data collection subscription request Information element Status Description Requestor ID M The identifier of the consumer...
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6.6.1.2.5 AI/ML energy consumption data collection subscription response
Table 6.6.1.2.5-1 describes information elements for the AI/ML energy consumption data collection subscription response from the ADAEC to the ADAES. Table 6.6.1.2.5-1: AI/ML energy consumption data collection subscription response Information element Status Description Result M The result of the AI/ML energy con...
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6.6.1.2.6 AI/ML energy consumption data notification
Table 6.6.1.2.6-1 describes information elements for the AI/ML energy consumption data notification from the ADAEC to the ADAES. Table 6.6.1.2.6-1: AI/ML energy consumption data collection notification Information element Status Description Subscription ID M The identifier for the subscription. Data Collection ...
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6.6.2 Architecture impacts
None.
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6.6.3 Solution evaluation
This solution addresses Key Issue #4 – open issue #1 on how to collect and use energy consumption data for AI/ML operations. The solution proposes enhancements to ADAE service described in 3GPP TS 23.436 [11] to support AI/ML energy consumption analytics. The solution enhances the ADAE service by generating analytics ...
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6.7.1 Solution Description
This solution introduces a new analytics event for "AIMLE client energy sustainability analytics" as requested from the Consumer who can be the VAL Server or AIMLE server to the ADAES. These analytics may be used for predicting whether an AI/ML client at the VAL UE can be considered a candidate in a ML training or infe...
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6.7.2 Architecture impacts
No architecture impact is expected.
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6.7.3 Solution evaluation
This solution addresses Key Issue #4, and in particular enhances SEAL ADAES to provide analytics related to the energy consumption sustainability for a given VAL or AIMLE service. The solution is feasible, well aligned with the ADAE functional architecture, and does not introduce additional dependencies on 3GPP networ...
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6.8.1 Solution Description
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6.8.1.0 General
This solution does not add new procedure. Instead, it proposes introducing a new VAL server policy in clause 9.5, 'Network slice optimization based on VAL server policy', 3GPP TS 23.435 [13]. The new policies enable NSCE server performs slice modifications based on monitoring energy-related information, such as energy ...
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6.8.1.1 Procedure
Figure 6.8.1.1-1 outlines the procedure, where Steps 1-4 represent existing operations. Step 5 introduces a new function in which the NSCE server monitors energy-related information for a network slice. Step 6 involves the NSCE server taking action to adjust the slice, either to conserve energy or to encourage the use ...
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6.8.1.2 Information Flows
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6.8.1.2.1 General
The following information flows are specified for VAL server policy.
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6.8.1.2.2 Policy of Reducing Energy Consumption
Table 6.8.1.2.2-1 shows the request sent by a consumer to an NSCE server for VAL server policy provisioning procedure. Table 6.8.1.2.2-1: Policy of reducing energy consumption Information element Status Description Policy O Reduce Energy Consumption >Area of interest M The service area for which the policy pr...
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6.8.1.2.3 Policy of Promoting renewable energy consumption
Table 6.8.1.2.3-1 shows the request sent by a consumer to an NSCE server for VAL server policy provisioning procedure. Table 6.8.1.2.3-1: Policy of Promoting renewable energy consumption Information element Status Description Policy O Promote renewable energy usage >Area of interest M The service area for whi...
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6.8.2 Architecture impacts
Architecture impact has been identified in clause 6.8.1.
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6.8.3 Solution evaluation
This solution addresses the open issues in Key Issue #5 by proposing a new VAL server policy. The new policies enable NSCE server performs slice modifications based on monitoring energy-related information, such as energy consumption and the renewable energy ratio, at the slice level. 6.9 Solution #9: Enhancements to ...
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6.9.1 Solution Description
In 3GPP TS 23.436 [11], the DN Energy Efficiency analytics, ADAES provides analytics on the energy consumption /efficiency of an edge platform (including the EESs / EASs). The DN energy analytics is performed per DNN/ DNAI and may be used to trigger the application server migration to different cloud. The analytics are...
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8.18 Procedure for supporting DN Energy Efficiency analytics
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8.18.1 General
This clause describes the procedure for DN energy consumption/efficiency analytics, where the analytics are performed based on data collected from one or more DNs and A-ADRF.
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8.18.2 Procedure
Figure 8.18.2-1 illustrates the procedure for DN energy efficiency analytics enablement solution. Pre-conditions: 1. Data producers (e.g. A-ADRF, EAS, EES, OAM, ESE Server) may be pre-configured with data producer profiles (as in Table 8.2.4.8-1) for the data they can provide. ADAES has discovered available data pro...
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8.18.3 Information flows
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8.18.3.1 General
The following information flows are specified for DN energy analytics based on clause 8.18.2.
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8.18.3.2 DN energy analytics request/subscription request
Table 8.18.3.2-1 describes information elements for the DN energy analytics request/subscription request from the VAL server to the ADAE server. Table 8.18.3.2-1: DN energy analytics request/subscription request Information element Status Description Analytics Consumer ID M The identifier of the analytics consum...
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8.18.3.3 DN energy analytics response/notification
Table 8.18.3.3-1 describes information elements for the DN energy analytics response/notification request from the VAL server to the ADAE server to the VAL server (or to the notification endpoints provided in the request/subscription request). Table 8.18.3.3-1: DN energy analytics response/notification Information el...
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8.18.3.4 Response to DN energy analytics request
Table 8.18.3.4-1 describes information elements for the ADAES responses to the analytics request to the consumer (e.g. VAL server). Table 8.18.3.4-1: Response to DN energy analytics request Information element Status Description Successful response (NOTE) O (NOTE) Indicates that the request was successful. > S...
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6.9.2 Architecture impacts
No architecture impact has been identified.
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6.9.3 Solution evaluation
This solution addresses the Key Issue #6 on enhance existing ADAE DN Energy Efficiency analytics to support energy savings. New analytics IDs on “Energy analytics per application service” and “Ratio of renewable energy analytics” are introduced to enable the consumer to get analytics on energy consumption or energy eff...
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6.10.1 Solution description
This solution addresses the KI #6. The following are the procedures to introduce how LMS subscribes the energy related information analysis from ADAES (clause 6.10.1.1) and how LMS utilizes the obtained energy related information analysis to reduce the energy consumption for the location services (clause 6.10.1.2).
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6.10.1.1 Procedure of LMS subscription for the energy related information analysis
Figure 6.10.1.1-1 illustrates the high-level procedure of the LMS subscription for the energy related information analysis. The LMS may subscribe to the ADAES for the analysis of energy related information. And ADAES needs to support the new energy related information (i.e. energy consumption information) analytics. ...
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6.10.1.2 Procedure of LMS adjusting the location reporting configuration to save the energy
Figure 6.10.1.2-1 illustrates the high-level procedure of LMS adjusting the location reporting configuration to save the energy consumption. Figure 6.10.1.2-1: Procedure of LMS adjusting the location reporting configuration to save the energy 1. Similar with step 1 of clause 9.3.5 in 3GPP TS 23.434 [14], the VAL se...
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6.10.2 Architecture Impacts
This solution has no impact on the existing architecture.
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6.10.3 Solution evaluation
This solution addresses the KI #6 which introduces how LMS in SEAL subscribes the energy consumption information analytics from ADAES as described in clause 6.10.1.1 and how LMS reduces the energy consumption for the location services per VAL UE to support the energy saving via utilizing the obtained energy consumption...
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6.11.1 Solution Description
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6.11.1.0 General
Common energy saving services, e.g., data collection and processing, energy monitoring, are needed to support various applications with energy saving requirements. Common energy saving services allows reuse of the collected/processed energy information for different application purposes, reduce signalling and avoid was...
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6.11.1.1 Functional Model
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6.11.1.1.1 General
The functional architecture enhancement for SEAL Enabler (Energy Saving) is based on the generic functional model specified in clause 6.2 of 3GPP TS 23.434 [14]. It is organized into functional entities to describe an architecture enhancement which addresses the support for energy saving aspects for vertical applicatio...
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6.11.1.1.2 Network Functional Model
Figure 6.11.1.1.2-1: Network functional model with energy saving enablement server/client Figure 6.11.1.1.2-1 illustrates the network functional model with SEAL Enabler (Energy Saving). In the vertical application layer, the VAL client communicates with the VAL server over VAL-UU reference point. The SEAL functional...
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6.11.1.2 Functional Entities Description
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6.11.1.2.1 General
The SEAL Enabler (Energy Saving) functional entities with energy saving assistance and management functions are described in the following subclauses.
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6.11.1.2.2 SEAL ESE client
The SEAL ESE client interacting with the VAL client to obtain such energy data/information. It also interacts with the SEAL ESE server. The ESE client supports the common energy saving services on energy data collection and energy monitoring.
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6.11.1.2.3 SEAL ESE server
The SEAL ESE server functional entity provides for energy saving assistance and management supported within the vertical application layer. The common energy saving services provided by the ESE server include: - Energy data collection and processing: Enables consumer to subscribe and receive notify on the energy data ...
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6.11.1.3 Reference Points Description
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6.11.1.3.1 General
The reference points for the functional model for assistance and management of energy saving are described in the following subclauses.
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6.11.1.3.2 ESE-UU
The interactions related to energy saving assistance and management functions between the ESE client and ESE server are supported by ESE-UU reference point. This reference point utilizes Uu reference point as described in 3GPP TS 23.401 [2] and 3GPP TS 23.501 [3]. ESE-UU reference point is used for VAL service signall...
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6.11.1.3.3 ESE-S
The interactions related to energy saving assistance and management functions between the VAL server(s) and the ESE server are supported by ESE-S reference point.
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6.11.1.3.4 ESE-C
The interactions related to energy saving assistance and management functions between the VAL client(s) and the ESE client(s) within a VAL UE are supported by ESE-C reference point.
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6.11.1.3.5 ESE-X
The interactions related to ESE enablement functions between ESE server and other SEAL servers.
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6.11.2 Architecture impacts
New functional architectures are introduced with Energy Saving Enablement (ESE) server/client for common energy saving functionalities. The corresponding reference points are given in clause 6.11.1.3.