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17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.1.3 Service flows | 1. The fleet of trucks belonging to L leave the logistic center located in the middle of the uninhabited region hundreds of kilometers northeast of the major city Erehwon. There are many devices located in this fleet. The trucks and their contents comprise a physically dense group of UEs, all communicating periodically with the network. This 'massive IoT' group leaves the coverage of the logistics center. The network coverage over the road through the uninhabited region is very sparse.
2. As the trucks proceed into extreme low coverage, the energy consumed to communicate with the IoT devices increases. This energy consumption increase is monitored by the 5G network and can be aggregated, e.g. at the slice level.
3. The 'green service' policy for the service provided to L includes a maximum energy consumption rate. At a certain point the IoT communication of the fleet exceeds this maximum energy consumption rate.
4. The policy indicates that latency can be traded off with energy consumption for service to L; the communication service is delay tolerant in this condition. As the energy consumption rate has exceeded the maximum, the latency is increased to enforce this policy. In effect, L's fleet receives very limited service, with high latency, even for a limited period of time, no service at all.
NOTE: This use case does not describe how latency is increased, but does assume that this increase will result in a reduction of energy consumption. It is possible to reduce energy consumption by offering less service.
The use case description does not define how operator M offers the 'green service'. One possibility is that the maximum energy consumption policy applies to all services for the subscription of a device deployed by L with operator M. This simple policy may not be appropriate if the UEs deployed by L use different kinds of services at different times. In this case, the policy would apply to specific services (service flows, etc.) A requirement at the service flow level is not pursued in this use case.
A further option is that specific network slices apply a 'green service' policy to all services communicating by means of that slice.
The use case does not describe how energy consumption is determined. There is related work in SA5 and RAN3 to determine energy consumption. If energy consumption cannot be determined at the granularity, e.g. of a specific service or network slice or even the aggregate energy consumption of a subscriber, it is still possible to identify the total energy consumption of different elements in the 5G network. It is therefore possible, at least in principle, to divide the total energy by the number of served sessions, subscribers, etc. 'Average consumption' of a node or cell or network slice, etc. is a course unit of measurement, and does not reflect the true energy consumption at the finer granularity, though it still can be a useful metric.
Though an averaging approach could be useful to count the total amount of energy used to attribute to each subscriber, this approach is not enough to measure the rate of energy consumption as described in this use case. For this, there would have to be finer granularity energy reporting than 'per node' or 'per cell.' Though this is not yet supported in the 5G network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.1.4 Post-conditions | The IoT devices in the fleet belonging to L are able to communicate with varying latency, depending on the energy consumption required to serve the devices. When the UEs are in poor coverage, they communicate seldom, when under good coverage, they can communicate more frequently.
The total energy consumption of M's network has reduced while still providing adequate service to customer L.
It is important to emphasize that there has been no trade-off between 'energy efficiency' and 'service quality.' Customer L received what was necessary while using less energy precisely because the energy consumption was taken into account in the service delivery. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.1.5 Existing feature partly or fully covering use case functionality | The 5G network can monitor energy consumption. The existing energy consumption monitoring is done at an O&M level, per network node, per cell and per network slice. The number of UEs per network node, cell and network slice are also known. Please see Annex A for an overview of existing energy efficiency standardization, which includes the determining energy consumption for use in calculating energy efficiency.
The 5G network can enforce performance criteria, as described in TS 22.261, 6.7 [15]. Most of the enforcement requirements refer to prioritization, but policies that result in other enforcement are possible too, e.g. gating, charging, credit control, restrictions with respect to maximum allowed resources, etc.
Gap: there is currently no means for the 5G network to determine the per subscriber or per network slice service flow energy consumption. This information is not included in network data analytic services. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.1.6 Potential new requirements needed to support the use case | [PR.5.1.6-1] Subject to operator’s policy, the 5G network shall support subscription policies that define a maximum energy consumption rate for services without QoS criteria (also termed "best effort" services.)
NOTE 1: The granularity of the subscription policies can either apply to the subscriber (all services), or to particular services. This requirement's applicability is limited to UEs that only support services without QoS criteria.
[PR.5.1.6-2] Subject to operator’s policy, the 5G network shall support enforcement of subscription policies that define a maximum energy consumption rate for services without associated QoS criteria (also termed "best effort" services.)
[PR.5.1.6-3] The 5G network shall support a means to define maximum energy consumption rate with specific granularities:
a) subscriber granularity (considering all services of the 5G network for the subscriber);
b) network slice granularity.
NOTE 2: The energy consumption of the UE is out of scope of this requirement.
[PR.5.1.6-4] Subject to operator's policy, the 5G network shall support energy consumption monitoring at per network slice and per subscriber granularity.
NOTE 3: Energy consumption monitoring as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirement does not imply that some form of 'real time' monitoring is required. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2 Use case on supporting different energy-related SLAs in industrial campus | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.1 Description | Industrial campuses are very typical scenarios of edge computing and local traffic offload. Dedicated network facilities are usually deployed near the campus for lower latency and local data protection. This brings a problem that these network facilities are used only for the campus, so while the manufacturing load is light or during vacation, these network facilities will be in very light load or even no load. Under this scenario, the energy consumption of these network facilities will be unnecessary. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.2 Pre-conditions | Factory F, a smart manufacturing factory locates in a remote area outside the city. Factory F requires low latency in AGV transporting services and local data processing using computing vision to support image comparison for fault detection in circuit boards. Factory F has an agreement with Operator T on the communication service with certain SLA. As the manufacturing activity is not consistent, Operator T provides a replaceable SLA which can be used during off-peak time. This replaceable SLA can reduce energy consumption by changing the energy state of network functions used locally (e.g. to “energy saving” state), and the action can be activated either by pre-configured policy or by notification from Factory F. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.3 Service flows | 1. Operator T provides a dedicate set of UPF and MEC platform for factory F. Factory F is an environmental conscious enterprise that cares about energy saving (and efficiency) along its whole industrial chain.
2. When the manufacturing load of Factory F reaches a certain threshold (lower or higher), which is evaluated by Factory F, a notification will be sent to Operator T.
3. Operator T will change the energy state of the dedicated network functions accordingly to energy saving, based on the pre-agreed policy with Factory F.
4. After one year of this kind of usage, the charging information of the communication service will consider the actual usage time of the different energy states. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.4 Post-conditions | Manufacturing of Factory F will be not affected, while energy consumption of the communication service could be saved by dynamically changing energy states of network functions, and the expenses of the communication service will be lower to encourage this kind of environmental-friendly action. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.5 Existing features partly or fully covering the use case functionality | In TS 28.310 [6], there are existing requirements to switch off edge UPFs during off-peak hours:
REQ-SOUPF-FUN-1: The management service producer responsible for energy saving should have the capability allowing its authorized consumer to collect the traffic load performance measurements of its edge UPFs.
REQ-SOUPF-FUN-2: The management service producer responsible for energy saving should have the capability allowing its authorized consumer to administratively prohibit selected edge UPFs from performing services for its users, either with immediate effect or only when no more users are using these UPFs. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.2.6 Potential new requirements needed to support the use case | [PR.5.2.6-1] The 5G system shall support different energy states of network elements and network functions.
[PR.5.2.6-2] The 5G system shall support dynamic changes of energy states of network elements and network functions, based on pre-configured policy with authorised 3rd party.
NOTE 1: Pre-configured policy may include: the time of changing energy states, which energy state map to which level of load, etc.
[PR.5.2.6-3] The 5G system shall support different charging mechanisms based on the different energy states of network elements and network functions. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3 Use case on energy consumption exposure considering possible deployment scenarios | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.1 Description | When considering Energy as a service or network performance criteria, it is necessary to consider different 5G network deployment scenarios, e.g. for RAN network with dual connectivity, RAN network with CU-DU deployment, RAN sharing, etc. That means whatever the deployment scenario, the energy consumption of the 5G network which relates to the industry customer is expected to be acquired and exposed to the authorized third parties. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.2 Pre-conditions | The network operator A deploys 5G network “N” to serve industry customers C and D.
In the 5G network “N”, some of the gNBs can support dual-connectivity. In order to achieve more flexible deployment and reduce the cost, operator A also deploys a large number of DUs in some hotspot area, each DU is for covering a certain area. For customer C, dual-connectivity is utilized, while for customer D, multiple DUs have been configured.
Industry customers C and D have also subscribed the “Green Energy Moni” value-added service from network operator A, thus they can access energy consumption information corresponding to their respective network functions from a web application provided by Operator A. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.3 Service flows | 1. The 5G network “N” of operator A acquires the energy consumption information of related 5G network functions serving customers C and D.
2. Customer C asks the “Green Energy Moni” of Operator A to provide the network energy consumption information associated with the 5G network functions serving it via dual-connectivity deployment.
3. Operator A provides the network energy consumption information to customer C.
4. Customer D asks the “Green Energy Moni” of Operator A to provide the network energy consumption information associated with the 5G network functions serving it via DU deployment.
5. Operator A provides the network energy consumption information to customer D. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.4 Post-conditions | Customers C and D can get the energy consumption information of the network functions serving them, independently from NG-RAN deployment scenarios. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.3.6 Potential new requirements needed to support the use case | [PR.5.3.6-1] Subject to operator’s policy and consent by the vertical customer, the 5G system shall be able to acquire energy consumption information of the network functions serving the customer, independently from NG-RAN deployment scenarios, and expose this information to the customer and authorized third parties. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4 Use case on energy efficiency information exposure under NPN RAN sharing | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.1 Description | In the practice of 5G NPN deployment, in order to save time and cost, RAN sharing (i.e. NG-RAN is shared by any combination of PLMNs and NPNs) is a common deployment scenario for vertical industries. The customers will concern about the energy efficiency of their communication service especially in RAN sharing cases. Thus, it is reasonable for 5G system to acquire and expose the energy efficiency information of the customer including when it is served by RAN sharing network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.2 Pre-conditions | The 5G network operator A deploys local NPN “N1” network in factories for customer C which is sharing resource of operator A’s PLMN “R”.
Customer C has subscribed the “Green energy Moni” value-added service for its NPN “N1” from network operator A, thus it can access energy efficiency information corresponding to the “N1” network from a web application provided by Operator A. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.3 Service flows | 1. The 5G network of operator A acquires the energy efficiency information of the NPN ”N1” and PLMN “R”.
2. Customer C asks the “Green Energy Moni” of Operator A to provide the energy efficiency information of its network “N1”.
3. The operator A acquires and provides energy efficiency information of the network “N1” to customer C. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.4 Post-conditions | Customer C can get the energy efficiency information of its network “N1”. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.5 Existing features partly or fully covering the use case functionality | TS 28.554 [12] already defines EE, EC and DV-related KPIs and use cases to acquire and calculate energy-efficiency at various levels within the 5G system. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.4.6 Potential new requirements needed to support the use case | [PR.5.4.6-1] Subject to operator’s policy and consent by the customer of NPN, the 5G system shall be able to acquire energy efficiency information of the NPN, including the shared network function(s) which is (are) serving the NPN, and expose this information to the NPN customer and authorized third parties. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5 Use case on service energy monitoring by an application server | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.1 Description | In this scenario, a service provider monitors events resulting from energy consumption policy triggers in the 5G system. These triggers correspond to monitoring policy in the 5G system as well as energy enforcement policies.
Figure 5.5-1: Monitoring of Energy Events by the 5G network for an AS
In Figure 5.5.1, the application server AS obtains information corresponding to the energy consequences of a UE 'A' served by the 5G network.
This use case will provide a description of a scenario in which the service provider (who operates an application server) cares about energy consumption in the 5G system as a result of the service to UE A. This could be for 3 reasons:
- the service provider needs to show they are saving energy;
- the service has an associated energy cost, and the service provider wants to reduce it. This is analogous to the use of industrial or consumer electronics when energy rates are lower, and also as an incentive to operate more efficiently;
- the service provider recognizes that there are policies that limit energy use (such as aggregate energy use of a network slice) and controls the overall use of the service to operate within those constraints.
The use case introduces five new concepts related to new energy events and energy event monitoring:
a) the ability for the network operator to create a 'maximum energy credit' policy, after which services are gated;
b) the ability for the network operator to inform an AS of the 'maximum energy credit expired' event;
c) the ability for the 5G system to calculate 'energy credit' use;
d) the ability to monitor and provide to the AS the use of 'energy credits' (or other energy 'quantum');
e) the support a new policy that establishes the energy consequence for charging control - either charging for use of energy or establishing an 'energy credit limit' for enforcement by the 5G system. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.2 Pre-conditions | The UE "A" has a subscription that enables it to make use of 'best effort communication subject to energy constraints' policy for communication. This class of communication was introduced in clause 5.1.
The application service provider of "AS" is capable monitoring service aspects of the 3GPP system, e.g. through network exposure of information as described in TS 22.261 [15] for QoS monitoring or TS 22.115 [16] related to credit limit policy and control. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.3 Service flows | 1. The application service provider of AS has an energy policy related to the service for the subscription related to UE "A". As a result, AS requests to monitor 'Energy Use', which is a kind of usage monitoring supported by the 5G system. The monitoring policy has an established 'threshold' for the 5G system to notify the AS.
In addition, the AS requests to monitor 'Out of Energy Credit' events.
2. The 5G system provides service to UE A according to a 'best effort communication subject to energy constraints' policy, where the policy charges for energy use and also imposes an 'energy credit' limit, after which the UE A subscription is 'gated' (receives no further services from the 5G system until more 'energy credit is available).
3. UE A proceeds to use services of the 5G system, especially data communication. As it does so, the charging system is triggered and generates records. The 3GPP charging system uses a means to identify how much credit is used and whether a credit limit is exceeded. The 3GPP charging system in this use case also uses a means of calculating energy credits on the basis of charging events. That is, there is a 'rating policy' used to multiply a 'charging event' by an 'energy consumption' unit.
NOTE 1: The actual amount of energy corresponding to an 'energy unit' used in energy credit control is out of scope of this use case. A mobile network operator can develop a model by which they analyze the total energy needed to provide services and assign fractions of these to each event triggered in the charging system.
4. When the total 'energy units' exceed the reporting threshold according to the energy monitoring policy, the 5G system exposes this energy consumption information to AS.
NOTE 2: Monitoring of energy consumption could be done by other means than 'energy units' corresponding to the same units as the credit limit. This could be useful for the third party. However, only by exposing units that result in charging or gating enforcement by the network operator can the third party determine the consequences of their use of services and potentially change their use of those services, e.g. to communicate sparingly, to communicate more efficiently (e.g. at times in less energy use is reported per 'byte', etc. of communication, as calculated by the third party based on their own measurements and the monitoring reports of the 5G system.)
5. When the total 'energy units' exceed the energy credit limit, this results in the 5G system exposing this event to the AS. The AS could take some action to restore energy credit, but this is out of scope of the use case. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.4 Post-conditions | The UE A's energy consumption can be monitored by AS. The AS can alter their activity (e.g. communicate less intensely or less frequently) to remain within their expectation - be it to keep the charging per energy consumption to their expectation, or to avoid exhausting A's energy credit limit.
The MNO is able to create and enforce policies that attach consequences to energy consumption. This can lead to energy efficient behaviour on the part of service providers which is both in their interest and the interest of the MNO. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.5 Existing feature partly or fully covering use case functionality | The 5G system provides support for credit limits [16, clause 8.2] and for performance monitoring [15]. There are a number of other events that are exposed by the 5G system to third parties by the Policy and charging control framework by the 5G System [17]. These events and their triggers, which are not detailed in stage 1, allow for usage monitoring to be exposed to a third party in specific circumstances, e.g. sponsored connectivity. The scenario in this use case is similar to sponsored connectivity, as the application service provider is a directly concerned party that seeks to operate successfully in an efficient manner, as there are charging and even gating consequences as the UE communicates with AS.
Note that the existing usage monitoring and reporting for sponsored connectivity is not sufficient to support this use case because these do not in any way take into account the energy consequence of the service. Only traffic volume and time-based monitoring are supported today. Other chargeable events (and therefore significant from an energy perspective) are not captured by usage monitoring as supported in the 5G system. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.5.6 Potential new requirements needed to support the use case | [PR.5.5.6-1] Subject to operator’s policy, the 5G system shall support subscription policies that define a maximum energy credit limit for services.
[PR.5.5.6-2] Subject to operator’s policy, the 5G system shall support subscription policies that support a means to associate energy consumption units with charging records.
[PR.5.5.6-3] Subject to operator’s policy, the 5G system shall support a means to expose energy consumption to authorized third parties for services, such that the energy consumption information clearly identifies the 'approaching' enforcement of an energy credit limit.
[PR.5.5.6-4] Subject to operator’s policy, the 5G system shall support a mechanism to perform energy consumption credit limit control for services.
NOTE 1: The result of the credit control is not specified by this requirement. Examples include gating, increased charging rates, etc.
NOTE 2: Credit control [18] compares against a credit control limit. In this use case, charging events are assigned a corresponding energy consumption and this is compared against a policy of energy credit limit. The use case assumes it is possible that there is a new policy to limit energy consumption allowed. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6 Use case on supporting service-level energy efficiency analysis for verticals | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.1 Description | Company A is located in an industrial campus. There are three internal applications used by employees for daily work which are based on two network slices. App A is for internal communication. App B is for production control. App C is for office automation. A and C are running on one slice, while B running on a separate slice. The data of these three applications are all dealt with a locally deployed UPF in this campus. The operator provides the additional service of exposing energy consumption of locally deployed UPF. Company A find that energy consumption of the UPF become higher recently, but cannot find out the cause, hope that 5G system can help to analysis which users or application are abnormal.
5G system analysis the data volume on this UPF and energy consumption of each app periodically.
Figure 5.6-1: Supporting service-level energy efficiency analysis for verticals |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.2 Pre-conditions | 5G system support energy consumption analysis based on data volume and energy consumption of network functions, which can be done by UPF. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.3 Service flows | 1.Company A finds abnormal energy consumption on the local network entity and request 5G system to report data usage of app A, B and C in past 3 days.
2.5G system analyses data volume and energy consumption of each app in every 2 hours.
3.5G system report shows that app B has a large data usage during 3am-5am every day.
4.Company A finds that app B has an abnormal setting which lead to system update repeatedly and large energy consumption. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.4 Post-conditions | Company A located the abnormal app and machine. They reset the setting and fix the problem. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.5 Existing features partly or fully covering the use case functionality | Requirements for DV measurement control and Power, Energy and Environmental (PEE) measurement has been defined to support for 5G NF measurement control.
In SA5 TS 28.554 [12], clause 6.7.3.3 Network Slice Energy Consumption are introduced.
In SA2, quota for PDU sessions per network slice and user numbers are already defined. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.6.6 Potential new requirements needed to support the use case | [PR.5.6.6-1] The 5G system shall support energy consumption measurement of network functions and exposure to authorised 3rd party.
NOTE: The granularity of energy consumption measurement could vary according to different situations, for example, when several services share a same network slice, etc. Energy consumption monitoring as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirement does not imply that some form of 'real time' monitoring is required. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7 Use case on energy consumption information exposure considering QoS | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.1 Description | Quality of service (QoS) refer to the network measurement of the overall performance about a communication service for the user. This network performance statistic can be e.g, packet loss, data rate, transmission delay, jitter, etc. When provide the energy as a service or a network performance criteria, e.g. in clause 5.2, the industrial park customer can be provided different energy-related SLAs under different energy states of network by operator, it is reasonable that not only the energy consumption information of the network or network functions but also the associated network performance statistic information are collected and exposed together to the customers or authorized third parties which will help customers to achieve more visible network service under different energy states of network functions.
The network performance statistic information can be pre-configured by the customer, authorized third parties or by Operator to be associated with the network functions energy consumption information. The network performance statistic information can be packet loss, data rate, transmission delay, jitter, etc. which can be collected and calculated the average value based on 5QI refer TS28.554. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.2 Pre-conditions | The network Operator deploys 5G NPN network in industrial park to provide energy as a service “GreenPark” for the industry park customer M. The “GreenPark” service can provide high data rate communication service and higher reliability service either. The industry customer M has subscribed the high data rate service with SLA “H”. The network Operator also provides a replaceable SLA “E2H” which can be used during off-peak working time. This replaceable SLA can reduce energy consumption by changing the energy state of a cell, a network element and/or a network function belong to the 5G NPN (e.g. to “energy saving” state), and the action can be activated either by pre-configured policy or by notification from customer M. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.3 Service flows | 1. Customer M asks the “GreenPark” Operator to provide the “GreenPark” energy consumption information and its communication services network performance statistic information (e.g. the data rate, packet delay and packet loss) per hour during the working time (e.g. from 9am to 5pm) in the industrial park.
2. The operator acquires the energy consumption information of the 5G NPN serving customer M every hour.
3. At the same time, operator collects the network performance statistic information (e.g. average data rate, average packet delay and average packet loss) from the 5G NPN serving customer M every hour.
4. The operator provides the energy consumption information of the 5G NPN serving the customer M and the network performance statistic information from the 5G NPN e.g. the average data rate, average packet delay and average packet loss during the working time in the industrial park.
5. According to the pre-configured policy with customer M, the Operator changes the energy state of the 5G network functions of the 5G NPN serving customer M for energy saving. The operator continues to acquire the energy consumption information and collects the network performance statistic information from the 5G NPN under new energy state and provides this information together to the customer M. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.4 Post-conditions | Customers M can get the not only the energy consumption information but also the average data rate, average packet delay and average packet loss from 5G NPN during the working time and off-peak working time. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.5 Existing features partly or fully covering the use case functionality | The QoS monitoring requirements have been specified in the TS22.261 section 6.23. But it has not any consideration on energy consumption. Some related requirements are listed below:
The 5G system shall be able to provide real time QoS parameters and events information to an authorized application/network entity.
NOTE 2: The QoS parameters to be monitored and reported can include latency (e.g. UL/DL or round trip), jitter, and packet loss rate.
The 5G system shall support different levels of granularity for QoS monitoring (e.g. per flow or set of flows)
The 5G system shall support an update/refresh rate for real time QoS monitoring with a specified value (e.g., at least one update per second)
In TR 28.829 [25], there are solutions of collect network information of energy utility via OA&M.
In TR28.913 [26], section 4.6, the key issue is to add reliability KPI into the URLLC network slice energy efficiency formula. In this key issue, the energy efficiency is calculated in the 3GPP domain, the related information is not exposed together to external. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.7.6 Potential new requirements needed to support the use case | [PR.5.7.6-1] Subject to Operator policy and consent by the customer, the 5G system shall be able to collect and expose to the authorized third party, through same update rate e.g. hourly or daily, the energy consumption information for the network functions serving the customer, together with the network performance statistic information for the services provided by that network functions.
NOTE: The network performance statistic information could be the data rate, packet delay and packet loss, etc.
[PR.5.7.6-2] Subject to Operator policy, the 5G system shall provide means for the trusted 3rd party, to configure which network performance statistic information (e.g. the data rate, packet delay and packet loss) for the communication service provided to the customer, needs to be exposed along with the energy consumption information of the network functions serving the customer. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8 Use case on Application energy efficiency monitoring | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.1 Description | Next generation mobile communication systems are expected to accommodate more demanding services, e.g., XR, AI/ML which will require much energy consumption at the device side as well as the network side. The impact on devices and the network to support these services will be huge and sometimes unpredictable.
When Operator A is deploying a communication service to meet the application service requirements (e.g. gaming app requirements), the customer (e.g. service provider or vertical) needs to make sure that the application service doesn’t consume significant energy for the end users as well as for the data network side.
Possible high energy consumption or low energy efficiency of the application service can lead to an application layer adaptation at the service provider’s domain to deal with this. An example of application layer adaptation would be to trigger the adaptation of the service level due to high expected energy consumption for the given application in a certain service area (e.g. edge service area).
The Application service Energy Efficiency (AEE) can be monitored and predicted at the 5GS and can be exposed as a monitoring event to the Service Provider to allow an application layer action. Such monitoring may relate to whether the AEE is sustainable for a given service area and time of the day, or can be provided when the energy consumption for the application service is reaching the upper bound (upper bound can be set based on the SLA). The monitoring result can be exposed either periodically or event-based (e.g. when upper threshold is reached as defined in Energy-related KPIs) subject to the application service provider’s requirement (based on the SLA). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.2 Pre-conditions | The service provider X wants to deploy an application service (e.g., gaming service) in a given service area and for a target number of users, where the service is expected to be communicated via 5G network “N” of the 5GS of operator A. The application service may have different service levels, which may be different KPIs associated with the service, and can correspond e.g., to different levels of automation or video quality targets.
The service provider X subscribes to the operator A for the “App EnergyEff Moni” feature with the requested service level(s) to monitor whether the application service is energy-efficient when using 5G system of operator A for the given service level(s).
The operator A and service provider X have agreed on certain energy efficiency target for the application service and optionally for given service levels. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.3 Service flows | 1. Service provider X asks the “App EnergyEff Moni” of Operator A to provide the predicted application service energy efficiency information for App Service #1 and one or more service modes for a given service area and time of the day.
2. The 5G system of operator A acquires the energy consumption information of related 5G system functions serving the App Service #1 of service provider X. Such information can be derived per application service and can include statistical data related to the application service energy consumption within a given service area.
Then, the 5G system of operator A calculates or predicts the AEE for the application service #1 and optionally the service mode X, based on the acquired energy consumption information.
3. Operator A exposes the calculated or predicted AEE for the application service #1 (and optionally the service mode X) to the Service Provider X.
4. Service Provider X configures or adapts the application service parameters based on the Operator A feedback. Such adaptation of the application service parameters can be for instance the application server re-location to an edge data network to enhance the energy efficiency for the application. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.4 Post-conditions | Service provider X can get the energy related statistics or predictions for the application service #1, independently from NG-RAN deployment scenarios, and this can help either adapting the application service parameters (e.g. service levels, application relocation) or configuring the application service in an energy-efficient manner. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.5 Existing features partly or fully covering the use case functionality | EE TS 28.310 [6] specifies the work in 3GPP related to energy efficiency. It specifies use cases relating to energy efficiency such as switching off edges UPFs for low-latency communication in certain geographical areas when no user is actively using them. Based on the scenarios the document presents requirements to be considered to support energy efficiency. The main requirements among them are requirements related to Power, Energy and Environmental measurements as well as requirements concerning energy saving.
This use case uses the existing 3GPP features as input for the application-level energy efficiency prediction, without providing an overlapping capability. In particular, the energy monitoring and optimization tasks in OAM cannot consider per application / session energy monitoring/predictions, and are limited to the energy calculation and monitoring per managed element (e.g. NG-RAN, UPF, network slice...). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.8.6 Potential new requirements needed to support the use case | [PR.5.8.6-1] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall be able to derive energy efficiency information for one or more application services, and expose energy efficiency information notifications to the application service provider.
NOTE: The granularity of energy efficiency information notifications could vary according to different situations, for example, application service energy consumption can be acquired based on means of averaging or applying a statistical model for the energy consumed by the application sessions within the application service in the service area, etc.
[PR.5.8.6-2] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall be able to provide means to predict the energy efficiency per application service, and expose the predicted energy efficiency information to the application service provider.
[PR.5.8.6-3] Based on operator policy and service agreement between the operator and application service provider, the 5G system shall enable the application service provider to subscribe, update, and unsubscribe for energy efficiency information notifications.
5.9 Use case on renewable energy consumption information exposure |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.1 Description | According to a recent GSMA report [20], all major operators have set up targets to reduce carbon intensity from 50% to 70% in next couple of years with the ultimate goal of achieving net-zero emissions. Though 5G NR offers improved energy-efficiency, new 5G use cases and the wider adoption of 5G NR will result in an increased number of sites and antennas, which may offset these gains if left unmitigated.
To address this, cut down on emissions and increase network efficiency, operators have an interest in powering their network using renewable energy sources to reduce emissions and enhance network efficiency. It is also important for operators to understand and track the proportion of energy consumed in their networks that is sourced from renewable sources, which can be made available to customers and authorized third parties. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.2 Pre-conditions | The network operator R has deployed a 5G network "N" and is promoting its services as "Green Energy". This is due to the fact that 60% (this could be any % number, 60% is just provided as an example) of the energy required for network operations is sourced from renewable resources. The government is providing tax credits to companies using renewable energy, and R provides its customers with information about the proportion of renewable energy consumed and renewable energy certificates (RECs) [21], if applicable.
Company X, which places a high value on environmental sustainability, has subscribed to R’s Green Energy services requesting for minimum ratio of renewable energy used for the communication service. R provides X with a dedicated slice (or NPN) guaranteeing this minimum ratio. R provides periodic reporting information regarding the percentage of renewable energy consumed. As a result, X is eligible to receive tax credits from the government for its purchase of renewable energy. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.3 Service flows | 1. Customer X subscribes to the ‘Green Energy’ service for its warehouse, provided by operator R.
2. The warehouse is served by a limited “X” number of base stations and the core network could be hosted in a central cloud location that is powered by renewable energy.
3. Operator R provides a dedicated network slice that utilizes a minimum 80% renewable energy for customer X’s NPN at their warehouse. The 5G system will not actively monitor the dedicated resources for energy consumption.
4. Operator R periodically calculates statistics about the ratio of renewable energy consumption of the network elements used within the customer X’s dedicated slice (or NPN).
5. Customer X receives periodic report every month regarding the ratio of renewable energy consumption from Operator R.
6. Operator R supplies customer X with the requested information.
7. Customer X can advertise that it is committed to a “Green Energy” and is using 80% renewable energy for the dedicated communications service at its warehouse. Additionally, Customer X can also claim tax credits from the government. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.4 Post-conditions | Customer X can get a dedicated network slice or NPN utilizing a minimum ratio of renewable energy used by the network serving its warehouse.
Customer X receives a periodic report on the ratio of renewable energy used by the network serving its warehouse. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.9.6 Potential new requirements needed to support the use case | [PR.5.9.6-1] Subject to operator’s policy, the 5G system shall enable the operation of a dedicated network above a minimum ratio of renewable energy as requested by an authorized 3rd party.
NOTE 1: This requirement does not imply that the 5G system will actively monitor the dedicated resources.
[PR.5.9.6-2] Subject to operator’s policy, the 5G system shall be able to provide to a 3rd party the reporting of the ratio of renewable energy used to provide dedicated communication service to the 3rd party on periodic basis.
NOTE 2: The reporting period could be set, e.g., on monthly or yearly basis. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10 Use case on supporting carbon-aware communication service | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.1 Description | Global warming caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. To achieve carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in communication capabilities of networks (e.g., 5GS) enables a wide range of services (e.g., AR/XR). However, the rising demand for communication services in turn triggers a rising demand for energy and a greater risk of an even higher resulting GHG footprint. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
The adoption of alternative sustainable sources of energy incl. renewable energy (e.g., solar, wind, hydropower, geothermy) and nuclear power could help offset the GHG footprint of energy generation based on fossil fuels, even though their corresponding environmental impact also need to be considered. From an ICT standpoint and, 3GPP system in particular, the energy used by network nodes can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources (Mother Nature’s dictate), the average GHG emissions per consumed energy unit varies substantially by time and location. Hence, it is critical to take temporal and spatial dimensions of energy sources into account to provide communication services not only for a better traceability of the energy sources used but in turn for enabling a more sustainable energy use.
In the following use case, telecom operator provides the estimation of carbon emissions for the services.
Note that ADEME, the French Agency for Ecological Transition, has introduced a methodological standard for the environmental assessment of digital services. [24] According to this standard, “internet service providers and telecoms operators (physical and virtual) for fixed and mobile networks must inform their subscribers of the amount of data consumed and indicate the equivalent in greenhouse gas emissions.” The objective is to communicate on a monthly bill the carbon impact of a subscriber using the mobile network of operator 1 in <Month YEAR> with a consumption of <DV> GB is: <X> g CO2 eq. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.2 Pre-conditions | Eva uses her XR device during the commute. This XR device receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal).
Carbon intensity, defined as the quantity of CO2 equivalent emission per unit of final energy consumption for an operational period of use (e.g., gCO2 per kW·h), is used to estimate the amount of carbon emissions incurred by the 5G system operations. Such carbon intensity information can be collected from a third party.
The operator A offers a “carbon-aware communication service” which provides the estimated carbon emissions of communication services. The estimation is based on the subscriber’s data volume, the operator’s energy consumption and the carbon intensity of network. The estimated carbon emissions information is exposed to the service provider B. Users can acquire the estimated carbon emissions from the service provider B.
Eva loves our planet, so she prefers to know how her requested services produce carbon emissions. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.3 Service flows | 1. Eva subscribes the communication service provided by operator A.
2. During the commute between the home and the workplace, Eva wears her XR device and enjoys the immersive entertainment via 5G system operated by operator A.
3. During the service time, the 5G system incurs carbon emissions due to the energy consumption.
4. The operator A collects the carbon intensity information of energy consumption from an authorized third party.
5. By "carbon-aware communication service”, the operator A calculates the estimated carbon emissions for the service and exposes the estimated carbon emissions result to the service provider B.
6. From the service provider B, Eva can know the estimation of carbon emissions for her requested service from the operator A. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.4 Post-conditions | Eva can enjoy low-carbon XR entertainment with the awareness of its environmental impacts. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.10.6 Potential new requirements needed to support the use case | [PR.5.10.6-1] Subject to user consent, operator policy and regulatory requirements, the 5G system shall be able to provide a mechanism to expose to the authorized third parties the energy efficiency information (e.g., including the estimated carbon emissions) related to a subscriber based on the subscriber’s data volume over a specific period of time, the operator’s energy consumption, and the carbon intensity of operator’s network.
NOTE 1: The carbon intensity of operator’s network can be provided by an authorized third party and can vary based on locations.
NOTE 2: The granularity of reporting (e.g., per month) is not discussed in this study.
5.11 Use case on Temporarily pooling communication services over a geographical area for energy saving |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.1 Description | One of the strategies to save energy within mobile networks is to shut down some RAN nodes at times of low usage. Eventually only one communication service would be used. Thus, there is a potential for further gain to be exploited by pooling the communication service on a local basis among operators at times of low usage.
Agreements could be put in place between operators so that in the low load periods (e.g., night time) only one of multiple mobile networks may be active in an area and will provide communication service to the subscribers of all networks, whereas the other networks can apply cell shutdown of their own infrastructure to obtain network energy savings.
Alternatively, based on risks of power outage nationwide/regionwide, regulators could ask operators to “optimize” their coverage e.g., shutdown some nodes in overlapping coverage areas during energy peak hours and/or in specific geographical areas, whilst still guaranteeing minimum coverage/service (in particular emergency calls).
This can also apply between NPN operators and/or with PLMN operators. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.2 Pre-conditions | - OP1 and OP2 are two PLMN operators.
- There is an overlap coverage between OP1 and OP2, which both provide mobile communication services to their subscribers on various bands.
- There are mutual agreements between OP1 and OP2 allowing them to provide communication services to the subscribers of the other network, in case it is not active in an area for low load. They define e.g. on a daily basis or specific locations a time when the communication service pooling starts and ends, and can include other parameters like preferred bands etc.
- OP3 operates an NPN dedicated to a factory around its campus, which is mainly used for IIoT purposes, but also for employees.
- There is a business agreement between the OP1 and OP3, i.e. OP3 users can be served by OP1 network (but not the other way around) based on certain conditions. At night, OP3 shuts down its network when the machines are off, as the little remaining traffic is generated by some employees staying late or overnight. The agreement requests OP1 to provide access to OP3 UEs during the night hours for this type of traffic.
- UE 1 belongs to OP1. UE 2 belongs to OP2. UE 3 belongs to OP3. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.3 Service flows | Figure 5.11-1: Basic service scenario of communication service pooling for energy saving
1) At 8PM, OP3 (“beneficiary” network) starts informing its currently served UEs within a specific area that it will shut down its network and request them to move to OP1 (“donor” network). It can also indicate the time when it will resume connectivity (e.g. 8AM).
2) OP1 accepts OP3’s UEs onto its network based on “EE-based communication service pooling” reason (it wouldn’t have without agreement).
3) Once OP3 detects no UE is served anymore on its network, it shuts down its network
4) On the next morning at 8AM, OP3 powers up its network again in that area
5) OP3 UEs return to OP3
6) OP1 stop serving OP3 UEs.
Furthermore, as this is an industrial campus area, traffic for OP2 is low this Saturday (only OP3 factory is working). Based on its EE KPIs in that area and according to the agreement with OP1, OP2 decides to shut down its cells until Monday morning 6AM with the same mechanism. OP1 starts serving OP2 UEs under its own network during this time. In this case the decision is dynamic and not only based on fixed times, but on other conditions, within the agreed conditions between operators (e.g., anytime during weekends). |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.4 Post-conditions | After OP2 and OP3 have shut down their networks, their subscribers can still be served via OP1.
OP2 subscribers under “EE-based communication service pooling” are not charged differently when served by OP1 network, with respect to when they are under OP2 network coverage. OP2 may be charged by OP1 as per their company agreement, e.g. based on a flat cost, per subscriber, data volume, duration etc.
OP3 may also be charged by OP1 as per their company agreement. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.5 Existing feature partly or fully covering use case functionality | Network sharing is an existing technique used to save resources across operators (see in clause 6.21 of TS 22.261), which could be leveraged for “communication service pooling” for energy saving purposes.
However, current network sharing agreements are mainly on a permanent basis with little flexibility in time and space. Indirect network sharing is a promising technique that can be considered for this use case.
Minimization of Service Interruption (MINT) as defined in clause 6.31 of TS 22.261 in another existing feature, which has specified that “UEs can obtain service in the event of a disaster, if there are PLMN operators prepared to offer service. The minimization of service interruption is constrained to a particular time and place. To reduce the impact to the 5G System and EPS of supporting Disaster Roaming, the potential congestion resulting from an influx or outflux of Disaster Inbound Roamers is taken into account.”. Requirements exist, e.g., “to provide means to enable a UE to access PLMNs in a forbidden PLMN list if a Disaster condition applies and no other PLMN is available except for PLMNs in the forbidden PLMN list”.
Disaster roaming is further specified in clauses 4.4.3.3.1 and 3.10 of TS 23.122.
However, this use case is not related to disaster condition. Furthermore, differently from disaster roaming, there may be no detection of failure of home PLMN by the UE, and the pooling (i.e., roaming) duration may be known in advance. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.11.6 Potential new requirements needed to support the use case | [PR.5.11.6-1] Subject to regulatory requirements and operators’ policies, the 5G system shall support temporary pooling of communication services of multiple operators on a single operator within a geographical area.
NOTE 1: policies may include predefined times/locations, energy consumption/efficiency thresholds, preferred bands etc.
[PR.5.11.6-2] Subject to regulatory requirements and operators’ policies, the 5G system shall enable an operator providing communication service pooling to serve UEs of other operators.
[PR.5.11.6-3] Subject to operators’ policies, the 5G system shall enable a UE to display the subscriber’s home operator network name during communication service pooling, even when this UE is served by another operator.
[PR.5.11.6-4] The 5G system shall be able to support collection of charging information associated with a UE served using communication service pooling. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12 Use case on supporting communication service with best-effort renewable energy consumption | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.1 Description | Climate change caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. Toward the goal of carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in cellular technologies (e.g., 5GS) that enable a wide range of applications has led to an explosive growth of service demands in networks. ICT sector is expected to account for 20% of the global energy consumption by 2040. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
To reduce the carbon footprint, telecom operators are utilizing more renewable energy (e.g., solar, wind) that does not release carbon dioxide when producing electricity. The energy used by network can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location.
In the following use case, telecom operator provides communication service considering the supply of renewable energy, in which operator utilizes renewable energy sources in a best-effort manner while ensuring the QoS levels of services to be met. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.2 Pre-conditions | Eva has video calls with her family during the commute. She receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal). The ratio of renewable energy is determined as the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit. Calculation of ratio of renewable energy is done by means of averaging or applying a statistical model.
The operator A offers a “green communication service option” for which the supply of renewable energy is additionally considered during the provision of the services to users. If the green communication service option is determined to be enabled by the operator A, the operator A utilizes renewable energy sources in a best-effort manner while ensuring the QoS levels of services still be met.
The operator A monitors the supply of renewables in 5GS and the network operates on different ratios of renewable energy over time. The operator may also report to user the statistics of ratio of renewable energy for providing the requested communication service.
Eva loves our planet, so she subscribes the green communication service option which utilize as much renewable energy as possible without sacrificing the quality of serve for her video calls.
NOTE: This green service ensures that QoS level criteria continues to be met (i.e., there is no trade-off between energy efficiency and service quality) since the usage of renewable energy is just a best effort attempt. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.3 Service flows | 1. During the commute, Eva has video calls with her family via the 5G system operated by operator A.
2. Eva subscribes the green communication service option provided by operator A, which ensures the QoS level of service to be met and utilize renewable energy sources in a best-effort manner.
3. The operator A monitors the supply of renewables for its 5G system, which varies substantially by time and/or location due to the highly variable and unpredictable nature of renewable energy sources.
4. During early morning, the operator A is able to provide communication service to Eva with 40% of ratio of renewable energy since solar power is plentiful and most of users don’t use services.
5. During the busy evening, many users request communication services at the same time, so the operator A is only able to provide communication service to Eva with 20% of ratio of renewable energy since the required energy consumption for network operation becomes more and the solar energy supply is decreasing.
6. Periodically, the operator reports to Eva the ratio of renewable energy for providing her communication service.
7. By "green communication service option” provided by operator A, the service requested by Eva use renewables as much as possible and Eva is still satisfied with the quality of video calls. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.4 Post-conditions | Eva can enjoy video calls with the satisfied quality of service while reducing her carbon footprint. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.12.6 Potential new requirements needed to support the use case | [PR.5.12.6-1] Subject to user consent and operator’s policy, the 5G system shall be able to expose to a subscriber the ratio of renewable energy used for the subscriber’s dedicated communication service on periodic basis.
[PR.5.12.6-2] The 5G system shall be able to collect charging information associated with a subscribed service based on the ratio of renewable energy used for providing the service.
NOTE: Calculation of ratio of renewable energy as described in the preceding requirements is done by means of averaging or applying a statistical model. The requirements do not imply that some form of 'real time' monitoring is required. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13 Use case on energy as service criteria for 5G environment adaptation | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.1 Description | It is becoming more important and challenging for operators and cloud/data service providers to reduce carbon emissions while providing for the best-in-class with optimal service plans to end-users. Many operators including cloud/data service providers run their services on top of multiple virtualized infrastructure environments with different hardware/software having various energy consumptions.
Often, operators are unaware of their own individual network functions’ power consumption or requirements, and how they behave with 5GS procedures for end-to-end service quality. Thus, operators should be able to measure and control their network functions with energy-based requirements.
In addition, individual network functions should be able to process, register, discover, select, load (re)balance and overload-control based on their current or predicted energy consumption. This would allow operators to fully control and optimize energy consumption internally, and/or based on various service plans for verticals and end-users. For example, using a ‘dynamic energy saving plan’ in mind, during a non-busy hour, the operator should be able to provide a service with a limited number of features, smaller capacity and/or relaxed SLA.
Figure 5.13-1: energy as service criteria for 5G environment adaptation |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.2 Pre-conditions | 5G system supports individual network functions monitoring of energy consumption.
It also supports for registration, discovery, selection, load-(re)balance and overload-control of individual network functions based on their energy consumption. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.3 Service flows | 1. David and John are subscribed to operator A with different service plans.
2. During operator’s A 5G service time over the 24 hours, depending on the number of subscribers and various service plans, the individual or groups of network functions are adapted, migrated and/or scaled based on their energy-efficiency requirements and plans.
3. Operator A has the ability to set their individual network functions to operate (e.g., for UE registration, NF selection, etc.) based on their current or predicted energy consumption.
4. By regularly measuring energy consumption of the individual network functions, operator A has the ability to fully optimize their energy savings whilst also maintaining a high service quality along with the time-of-the day. Based on how their network functions behave with energy-saving characteristics and controls, they can provide means to coordinate the operation of individual network functions to target global optimization of energy consumption within the 5G network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.4 Post-conditions | David is satisfied and enjoys his lower pricing plan with the awareness of carbon emission.
Operator A is also satisfied because it has the ability to manage (e.g., load balance) its network functions and adapt their procedures based on energy-saving characteristics. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.13.6 Potential new requirements needed to support the use case | [PR.5.13.6.1] Subject to operator policy and regulatory requirements, the 5G system shall be able to provide a mechanism for one or more network functions to operate based on energy consumption to meet various end-user’s service requirements.
[PR.5.13.6.2] Subject to operator policy and regulatory requirements, the 5G system shall be able to provide means to coordinate the operation of individual network functions to target optimization of energy consumption within the 5G network. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14 Use case on reducing GHG footprint of Application Services | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.1 Description | Global warming caused by excessive emissions of GHG (e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. To achieve carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in communication and computing capabilities of networks (e.g., 5GS, cloud services) enables offloading tasks to networked and distributed computing nodes (e.g., edge computing, cloud computing) for a wide range of services. However, the rising demand for such services in turn triggers a rising demand for energy and a greater risk of an even higher resulting GHG footprint. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
The adoption of alternative sustainable sources of energy incl. renewable energy (e.g., solar, wind, hydropower, geothermy) could help offset the GHG footprint of energy generation based on fossil fuels, even though their corresponding environmental impact also need to be considered. From an ICT standpoint and, 3GPP system in particular, the energy used by computing nodes in networks can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location. Hence, it is critical to take temporal and spatial dimensions of energy sources into account to accomplish compute tasks not only for a better traceability of the energy sources used but in turn for enabling a more sustainable energy use to achieve those tasks.
Up until now usually a system is designed to finish compute tasks as soon as possible (high throughput) and indicate results to the requester as soon as possible (low latency). However, some compute tasks have flexibility in both when and where they are executed, i.e., such type of workload could be executed in any computing node and tolerate some delays if the workload gets completed within certain given deadline. For example, some of AI/ML training, simulation, and video processing tasks might not require a quick response, which would allow flexibility to delay the execution of the related workloads in a computing node until, e.g., the utilized energy is deemed satisfactory in terms of GHG emissions. Such flexibility further allows to route workloads to a computing node using the (most) sustainable energy sources at that moment. As part of service, 3GPP system is able to execute compute tasks in a sustainable way by leveraging such flexibility.
In addition, consuming the renewable energy immediately when they are available, instead of storing them for the future use (e.g., in a big battery system), can also bring some economic benefits to operators or service providers, because this can reduce the cost and investment for scaling the energy storage system needed by the overall system.
In the following use case, by considering the temporal and spatial information of sustainable energy source and availability, the possibility of reduction of the GHG footprint for application services is explored. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.2 Pre-conditions | The operator A provides the computing services through the computing nodes owned by itself or other third-party companies via certain Service Level Agreement (SLA), which execute the compute tasks (e.g., offloaded by users). Each computing node is powered by renewable energy (e.g., solar energy), non-renewable energy (e.g., coal) or both. The highly variable nature of renewable energy sources makes the resulting GHG emissions by each computing node varies considerably by time and location. The high cost of large-scale energy storage system (e.g., battery system) also brings the incentive to the operator to consume the renewable energy immediately when it is produced (e.g., to reduce the cost for building the needed battery system). The ratio of renewable energy measures the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit.
NOTE: Computing node is the resource to execute compute tasks belong to service provider, e.g., computing node can be a Server node hosted by an Edge Computing Service Provider (ECSP) based on PLMN operator service agreement. Alternatively, ECSP and the PLMN operator can be part of the same organization.
Eva is an AI engineer who needs to train some AI/ML models for her research work. Eva has collected all the needed data (e.g., the images of cats and dogs) during the weekdays. To train this model, the required dataset must be sent to a computing node, and the node will train the specified model (e.g., a dog/cat classifier) over this dataset. Eva needs to get the training result at the beginning of workday next week. Her compute tasks for AI/ML model training are offloaded to the system owned by the operator A for execution.
The operator A offers a “green compute and communication service” which can decide when and where the offloaded tasks are computed to reduce the overall GHG footprint of the system. This green compute and communication service requires tolerated deadline of compute task specified by the user, i.e., the quality of experience is not degraded as long as the compute task is finished within the given deadline. Eva loves our planet, so she is using this service for reducing the GHG footprint of her research work. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.3 Service flows | 1. Eva subscribes the green compute and communication service to save our planet.
2. Eva indicates to the operator A that the compute task needs to be finished before the next workday (8:00 AM on Monday).
3. Eva offloads the compute task of AI/ML model training to the system owned by the operator A before she left the office (7:00 PM on Friday) in New York.
4. In the operator A’s system, the "computing node NY" (i.e., the computing farm located in New York) is the closest computing resource to the Eva’s workplace. Traditionally the "computing node NY" is selected to execute Eva’s task immediately; however, there is no solar power in New York at this moment (i.e., the ratio of renewable energy is low).
5. If Eva’s AI/ML model is trained by the "computing node NY", it will result in some GHG emissions to the air which is not friendly to the environment.
6. Fortunately, the "green compute and communication service" has two alternative options for the execution of Eva’s compute task based on the ratio of renewable energy reported by the "computing node NY" and another node "computing node LA" located in Los Angeles:
◦ [Option 1: Greener Location] The "computing node LA" located in Los Angeles (is on 4:00 PM) having abundant solar energy at that moment (i.e., the ratio of renewable energy is high). The dataset can be sent to "computing node LA" and the results are sent back to Eva after the completion. Since the execution will not last over one day, the system can adopt this option even if it requires more time for the communications.
◦ [Option 2: Greener Time] The "computing node NY" will have plentiful solar energy during the period of 9:00 AM – 4:00 PM every day. The training executed during the daytime of the weekend will not generate any GHG emissions. Since the task can be finished before the next workday, the system can adopt this option to schedule the training to be executed during the weekend.
In addition, by consuming the renewable energy immediately when it is produced, the operator can reduce the scale of its renewable energy storage system and reduce the overall cost.
7. By adopting the either option provided by "green compute and communication" service, the execution of AI model training requested by Eva can be nearly carbon-free and Eva still obtains the desired training result before the deadline. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.4 Post-conditions | Eva’s AI/ML model training is finished before the targeted deadline while protecting our beautiful planet.
Operator A reduces the scale of its renewable energy storage system and reduce the overall cost. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.14.6 Potential new requirements needed to support the use case | [PR.5.14.6-1] Subject to operator’s policy and agreement between an application service provider and operator, the 5G system shall support a mechanism for the application service provider (including edge computing service provider) to provide to the 5G system the current or predicted ratio of renewable energy used for providing application services on periodic basis.
[PR.5.14.6-2] Subject to user consent and operator policy, the 5G system shall provide a mechanism to support the selection of an application server (including edge application server) based on the ratio of renewable energy for providing application services.
NOTE: An application server (including edge application server) can be a server node hosted by an Edge Computing Service Provider (ECSP) based on PLMN operator service agreement. Alternatively, ECSP and the PLMN operator can be part of the same organization. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15 Use case on supporting communication service with carbon-aware service requirements | |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.1 Description | Climate change caused by excessive emissions of GHG (Green House Gas, e.g., carbon dioxide) due to human activity (e.g., burning fossil fuels for electricity generation) is the main driver to climate change, which poses a significant threat to society and the environment. Toward the goal of carbon neutrality, it is important to reduce the GHG incl. carbon emissions in the first place rather than offset them later. Recent advancements in cellular technologies (e.g., 5GS) that enable a wide range of applications has led to an explosive growth of service demands in networks. ICT sector is expected to account for 20% of the global energy consumption by 2040. 3GPP plays a crucial role in the ICT sector to enable the deployment of these technologies on a global scale and therefore must also play a central role in enabling a sustainable future.
One key approach for telecom operators to reduce their carbon footprint is utilizing more renewable energy (e.g., solar, wind) that does not release carbon dioxide when producing electricity. The energy used by network can be from varied energy with different related levels of environmental impact incl. GHG emissions. Due to the highly variable and unpredictable nature of renewable energy sources, the supply of renewable energy varies substantially by time and location.
In the following use case, telecom operator provides communication service with carbon-aware requirements considering the ratio of renewable energy and the subscriber’s preferences. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.2 Pre-conditions | Eva watches videos during the commute. She receives 5G service from the mobile network operator A.
The 5G system operated by operator A is powered by both of renewable energy (e.g., solar energy) and non-renewable energy (e.g., coal). The ratio of renewable energy measures the ratio of the power that is used from renewable energy sources as a percentage of total power usage in a given time unit. Calculation of ratio of renewable energy is done by means of averaging or applying a statistical model.
The operator A offers a “green communication service option”, in which the service has adaptable QoS levels considering the ratio of renewable energy and the subscriber’s preferences, e.g., the operator A can provide a communication service with bit rate of 30Mbps and low ratio of renewable energy, which can be adapted to the service with bit rate is 10Mbps when high ratio of renewable energy is more desirable to the subscriber.
The operator A monitors the supply of renewables for its 5G system and adjust the operation of communication services. Following the pre-agreed QoS requirements with a subscriber, the operator A adjusts the communication services based on the supply of renewable energy.
Eva loves our planet, so she subscribes the optional green communication service. Therefore, the operator can determine to use a higher latency but greener network function entities (e.g., located in a faraway but powered by 80%+ renewable energy large scale computing/communication center) to provide services to Eva.
NOTE: This green service ensures that QoS level criteria continues to be met (i.e., there is no trade-off between energy efficiency and service quality) since all the adapted QoS levels are satisfied by the subscriber based on the pre-agreement. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.3 Service flows | 1. During the commute between the home and the workplace, Eva watches videos via 5GS operated by operator A.
2. Eva subscribes the green communication service option provided by operator A. Following the pre-agreed QoS requirements with Eva, the operator A adjusts the communication services based on the supply of renewable energy. That is, Eva is satisfied with all the adapted QoS levels based on this agreement when watching videos.
3. The operator A monitors the supply of renewables for its 5GS, i.e., the ratio of renewable energy (i.e., the ratio of the power that is used from renewable energy sources as a percentage of total power usage).
4. During the daytime, since solar power of a remote computing/communication center is plentiful, Eva gets video streaming with bit rate of 10Mbps, and the service provided by operator A has 40% for the ratio of renewable energy.
5. During the busy evening time, since the supply of solar power is decreasing, Eva gets video streaming with bit rate of 25Mbps, and the service provided by operator A has 10% for the ratio of renewable energy.
6. By "green communication service option” provided by operator A, the service requested by Eva use renewable as much as possible and Eva is still satisfied with the video content. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.4 Post-conditions | Eva can enjoy communication service with the satisfied quality of service while protecting our beautiful planet. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.5 Existing features partly or fully covering the use case functionality | None. |
17e8174f94d72a34a3d8a81dbfebc7a5 | 22.882 | 5.15.6 Potential new requirements needed to support the use case | [PR.5.15.6-1] Subject to user consent and operator policy, the 5G system shall be able to provide means to adapt a communication service to fulfil the subscriber’s preference concerning the ratio of renewable energy used for providing the service.
NOTE: Calculation of ratio of renewable energy as described in the preceding requirement is done by means of averaging or applying a statistical model. The requirement does not imply that some form of 'real time' monitoring is required. |
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