



Getting Ready for Energy-Efficient Networking                 E. Stephan
Internet-Draft                                                    Orange
Intended status: Informational                                M. Palmero
Expires: 26 July 2026                                         Individual
                                                               B. Claise
                                                                   Q. Wu
                                                                  Huawei
                                                         L. M. Contreras
                                                              Telefonica
                                                         C. J. Bernardos
                                        Universidad Carlos III de Madrid
                                                                 X. Chen
                                                            China Mobile
                                                         22 January 2026


               Use Cases for Energy Efficiency Management
                     draft-ietf-green-use-cases-01

Abstract

   This document groups use cases for Energy efficiency Management of
   network devices.

   Discussion Venues

   Source of this draft and an issue tracker can be found at
   https://github.com/emile22/draft-ietf-green-use-cases

About This Document

   This note is to be removed before publishing as an RFC.

   The latest revision of this draft can be found at
   https://emile22.github.io/draft-ietf-green-use-cases/draft-ietf-
   green-use-cases.html.  Status information for this document may be
   found at https://datatracker.ietf.org/doc/draft-ietf-green-use-
   cases/.

   Discussion of this document takes place on the Getting Ready for
   Energy-Efficient Networking Working Group mailing list
   (mailto:green@ietf.org), which is archived at
   https://mailarchive.ietf.org/arch/browse/green/.  Subscribe at
   https://www.ietf.org/mailman/listinfo/green/.

   Source for this draft and an issue tracker can be found at
   https://github.com/emile22/draft-ietf-green-use-cases.




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Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

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   This Internet-Draft will expire on 26 July 2026.

Copyright Notice

   Copyright (c) 2026 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (https://trustee.ietf.org/
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
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   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   5
   2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   5
     2.1.  Incremental Application of the GREEN Framework  . . . . .   5
       2.1.1.  Use Case Description  . . . . . . . . . . . . . . . .   5
       2.1.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .   7
       2.1.3.  The Need for Energy Efficiency  . . . . . . . . . . .   7
       2.1.4.  Requirements for GREEN WG . . . . . . . . . . . . . .   7
     2.2.  Selective reduction of energy consumption in network parts
            proportional to traffic levels . . . . . . . . . . . . .   7
       2.2.1.  Use Case Description  . . . . . . . . . . . . . . . .   7
       2.2.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .   8
       2.2.3.  The Need for Energy Efficiency  . . . . . . . . . . .   8
       2.2.4.  Requirements for GREEN WG . . . . . . . . . . . . . .   8
     2.3.  Reporting on Lifecycle Management . . . . . . . . . . . .   8
       2.3.1.  Use Case Description  . . . . . . . . . . . . . . . .   8



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       2.3.2.  Carbon Reporting  . . . . . . . . . . . . . . . . . .   8
       2.3.3.  Energy Mix  . . . . . . . . . . . . . . . . . . . . .   9
       2.3.4.  GREEN WG Charter Specifics  . . . . . . . . . . . . .   9
       2.3.5.  The Need for Energy Efficiency  . . . . . . . . . . .   9
       2.3.6.  Requirements for GREEN WG . . . . . . . . . . . . . .   9
     2.4.  Real-time Energy Metering of Virtualised or Cloud-native
            Network Functions  . . . . . . . . . . . . . . . . . . .   9
       2.4.1.  Use Case Description  . . . . . . . . . . . . . . . .   9
       2.4.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .   9
       2.4.3.  The Need for Energy Efficiency  . . . . . . . . . . .  10
       2.4.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  10
     2.5.  Indirect Energy Monitoring and control  . . . . . . . . .  10
       2.5.1.  Use Case Description  . . . . . . . . . . . . . . . .  10
       2.5.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .  10
       2.5.3.  The Need for Energy Efficiency  . . . . . . . . . . .  10
       2.5.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  11
     2.6.  Consideration of other domains for obtention of end-to-end
            metrics  . . . . . . . . . . . . . . . . . . . . . . . .  11
       2.6.1.  Use Case Description  . . . . . . . . . . . . . . . .  11
       2.6.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .  11
       2.6.3.  The Need for Energy Efficiency  . . . . . . . . . . .  11
       2.6.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  12
     2.7.  Dynamic adjustment of network element throughput according
            to traffic levels in wireless transport networks . . . .  12
       2.7.1.  Use Case Description  . . . . . . . . . . . . . . . .  12
       2.7.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .  12
       2.7.3.  The Need for Energy Efficiency  . . . . . . . . . . .  12
       2.7.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  13
     2.8.  Video streaming use case  . . . . . . . . . . . . . . . .  13
       2.8.1.  Use Case Description  . . . . . . . . . . . . . . . .  13
       2.8.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .  14
       2.8.3.  The Need for Energy Efficiency  . . . . . . . . . . .  14
       2.8.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  14
     2.9.  WLAN Network Energy Saving  . . . . . . . . . . . . . . .  14
       2.9.1.  Use Case Description  . . . . . . . . . . . . . . . .  14
       2.9.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . .  16
       2.9.3.  The Need for Energy Efficiency  . . . . . . . . . . .  16
       2.9.4.  Requirements for GREEN WG . . . . . . . . . . . . . .  16
       2.9.5.  The Need for Energy Efficiency  . . . . . . . . . . .  17
       2.9.6.  Requirements for GREEN WG . . . . . . . . . . . . . .  17
     2.10. Fixed Network Energy Saving . . . . . . . . . . . . . . .  17
       2.10.1.  Use Case Description . . . . . . . . . . . . . . . .  17
       2.10.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  18
       2.10.3.  The Need for Energy Efficiency . . . . . . . . . . .  18
       2.10.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  18
     2.11. Energy Efficiency Network Management  . . . . . . . . . .  19
       2.11.1.  Use Case Description . . . . . . . . . . . . . . . .  19
       2.11.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  19



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       2.11.3.  The Need for Energy Efficiency . . . . . . . . . . .  19
       2.11.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  19
     2.12. ISAC-enabled Energy-Aware Smart City Traffic
            Management . . . . . . . . . . . . . . . . . . . . . . .  20
       2.12.1.  Use case description . . . . . . . . . . . . . . . .  20
       2.12.2.  GREEN WG Specifics . . . . . . . . . . . . . . . . .  20
       2.12.3.  Requirements for GREEN WG  . . . . . . . . . . . . .  21
     2.13. Double Accounting Open issue  . . . . . . . . . . . . . .  22
       2.13.1.  Use case description . . . . . . . . . . . . . . . .  22
       2.13.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  22
       2.13.3.  The Need for Energy Efficiency . . . . . . . . . . .  22
       2.13.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  22
     2.14. Energy Efficiency Under Power Shortage  . . . . . . . . .  22
       2.14.1.  Use case description . . . . . . . . . . . . . . . .  23
       2.14.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  23
       2.14.3.  The Need for Energy Efficiency . . . . . . . . . . .  23
       2.14.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  24
     2.15. Energy-Efficient Management of Distributed AI Training
            Workloads  . . . . . . . . . . . . . . . . . . . . . . .  24
       2.15.1.  Use Case Description . . . . . . . . . . . . . . . .  24
       2.15.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  24
       2.15.3.  The Need for Energy Efficiency . . . . . . . . . . .  24
       2.15.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  24
     2.16. Network-level Cross Layer Energy Saving . . . . . . . . .  25
       2.16.1.  Use Case Description . . . . . . . . . . . . . . . .  25
       2.16.2.  GREEN WG Charter Specifics . . . . . . . . . . . . .  25
       2.16.3.  The Need for Energy Efficiency . . . . . . . . . . .  26
       2.16.4.  Requirements for GREEN WG  . . . . . . . . . . . . .  26
   3.  Security Considerations . . . . . . . . . . . . . . . . . . .  26
   4.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  26
   5.  Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .  27
   6.  Use Cases Living List . . . . . . . . . . . . . . . . . . . .  27
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  27
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  27
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  27
   8.  Appendix I: Template preparation  . . . . . . . . . . . . . .  28
     8.1.  Use Case Description  . . . . . . . . . . . . . . . . . .  28
     8.2.  GREEN WG Charter Specifics  . . . . . . . . . . . . . . .  28
       8.2.1.  The Need for Energy Efficiency  . . . . . . . . . . .  28
     8.3.  Requirements for GREEN  . . . . . . . . . . . . . . . . .  28
   9.  Appendix II: Necessity and Impact of a Framework for Energy
           Efficiency Management . . . . . . . . . . . . . . . . . .  30
     9.1.  Framework Necessity . . . . . . . . . . . . . . . . . . .  30
     9.2.  Use Cases Calling for a Framework . . . . . . . . . . . .  31
     9.3.  Impact on Energy Metrics  . . . . . . . . . . . . . . . .  31
     9.4.  Current Device Readiness  . . . . . . . . . . . . . . . .  32
     9.5.  Why Now?  . . . . . . . . . . . . . . . . . . . . . . . .  32
   10. Informative References  . . . . . . . . . . . . . . . . . . .  33



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   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  34

1.  Introduction

   This document groups use cases collected from operators and from
   discussions since the GREEN WG preparations.

   It provides a set of use cases for Energy efficiency Management of
   network devices.  The scope is devices like switches, routers,
   servers and storage devices having an IP address providing a
   management interface.  It includes their built-in components that
   receive and provide electrical energy.

   In annex we recall the framework where the use cases can be put in
   situation.

2.  Use Cases

   This section describes a number of relevant use cases with the
   purpose of elicit requirements for Energy Efficiency Management.
   This is a work in progress and additional use cases will be
   documented in next versions of this document.  Use cases which are
   not tied enough to the current GREEN chater will be moved to the
   GREEN WG wiki pages or to other WGs or RGs.

2.1.  Incremental Application of the GREEN Framework

2.1.1.  Use Case Description

   This section describes an incremental example [legacy-path] of usage
   showing how a product, a service and a network can use the framework
   in different settings.

   This use case is the less trendy of all the use cases by far as its
   ambitious is limited to migration and coexistence, as usual.
   Nevertheless from a telco perspective, it is the centrality for 2
   main reasons:

   *  to start immediatly the move to energy efficiency using legacy
      devices;

   *  to account the gain of energy efficiency during incremental
      deployment of energy efficient network components;








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   Legacy routers, equipped with traditional Ethernet ports and optical
   interfaces will continue to operate within the network.  As part of
   broader sustainability and energy efficiency goals, there is interest
   in exploring the incremental integration of such devices into energy
   efficiency framework deployments.

   Two directions are considered:

   *  Improving energy efficiency of legacy devices through targeted
      upgrades such as replacing line cards, optimizing firmware
      behavior, or reconfiguring interface usage based on operational
      demand.

   *  Including legacy devices in early phases of energy-aware system
      deployment, ensuring that improvements are not limited only to new
      hardware generations.

   Legacy devices can still contribute to reducing overall power
   consumption and lowering resource usage and associated environmental
   impact.  Supporting these incremental improvements helps bridge the
   gap between existing infrastructure and modern energy-aware network
   strategies.

   Device moving gradually to GREEN energy efficiency supports:

   *  step 1 "baseline" : establishing a reference point of typical
      energy usage, which is crucial for identifying inefficiencies and
      measuring improvements over time.  At this step the controler use
      only the (c) part of the framework.  It is collected from the
      datasheet.

   By establishing a baseline and using benchmarking, you can determine
   if your networking equipment is performing normally or if it is "off"
   from expected performance, guiding you in making necessary
   improvements.

   The initial measurement of your networking equipment's energy
   efficiency and performance, aka Baselining, needs to be in
   coordination with the vendor specifications and industry standards to
   understand what is considered normal or optimal performance. example:
   Baseline: Your switches operate at 5 Gbps per watt.  Benchmarking:
   Vendor specification is 8 Gbps per watt; industry standard is 10 Gbps
   per watt.  Action: Implement energy-saving measures and upgrades.
   Tracking: Measure again to see if efficiency improves towards 8-10
   Gbps per watt.

   *  step 2 "component": part of the device hw or sw migrated to
      support GREEN framework elements.



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   *  step 3 "device controleur"

   *  step 4 "network level"

2.1.2.  GREEN WG Charter Specifics

   This use case demonstrates how Energy Efficiency can be incrementally
   applied and measured in legacy networks.

2.1.3.  The Need for Energy Efficiency

   Ensures that energy efficiency can be deployed, operated and measured
   per components, without waiting for full infrastructure upgrades.

2.1.4.  Requirements for GREEN WG

   *  Baseline Measurement: Ability to establish reference energy usage
      per device (from datasheets or monitoring).

   *  Component-Level Upgradability: Support partial migration of device
      subsystems to GREEN-aware models.

   *  Legacy Compatibility: Ensure the framework can include legacy
      equipment alongside GREEN-enabled devices.

   *  Energy Saving Validation: Mechanisms to measure and verify actual
      energy savings over time.

   *  Protection from Overuse: Avoid frequent power cycling that may
      damage sensitive components like lasers or connectors.

2.2.  Selective reduction of energy consumption in network parts
      proportional to traffic levels

2.2.1.  Use Case Description

   Traffic levels in a network follow patterns reflecting the behavior
   of consumers.  Those patterns show periodicity in the terms of the
   traffic delivered, that can range from daily (from 00:00 to 23:59) to
   seasonal (e.g., winter to summer), showing peaks and valleys that
   could be exploited to reduce the consumption of energy in the network
   proportionally, in case the underlying network elements incorporate
   such capabilities.  The reduction of energy consumption could be
   performed by leveraging on sleep modes in components up to more
   extreme actions such as switching off network components or modules.
   Such decisions are expected to no impact on the service delivered to
   customers, and could be accompanied by traffic relocation and / or
   concentration in the network.



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2.2.2.  GREEN WG Charter Specifics

   This use case fits within the GREEN WG's objectives by emphasizing
   energy-aware operational adjustments across network infrastructure
   that optimize energy use based on traffic loads and the intelligent
   activation/deactivation of resources.

2.2.3.  The Need for Energy Efficiency

   Reducing energy usage during during low-demand periods can lower
   operational costs and carbon emissions while also prolonging
   equipment lifespan.

2.2.4.  Requirements for GREEN WG

   *  Support for device and component-level sleep, standby, and
      hibernation modes.

   *  Component-level control (e.g., ports, modules).

2.3.  Reporting on Lifecycle Management

2.3.1.  Use Case Description

   Lifecycle information related to manufacturing energy costs,
   transport, recyclability, and end-of-life disposal impacts is part of
   what is called "embedded carbon."  This information is considered to
   be an estimated value, which might not be implemented today in the
   network devices.  It might be part of the vendor information, and to
   be collected from datasheets or databases.  In accordance with ISO
   14040/44, this information should be considered as part of the
   sustainable strategy related to energy efficiency.  Also, refer to
   the ecodesign framework [(EU) 2024/1781] published in June by the
   European Commission.

2.3.2.  Carbon Reporting

   To report on carbon equivalents for global reporting, it is important
   to correlate the location where the specific entity/network element
   is operating with the corresponding carbon factor.  Refer to the
   world emission factor from the International Energy Agency (IEA),
   electricity maps applications that reflect the carbon intensity of
   the electricity consumed, etc.








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2.3.3.  Energy Mix

   Energy efficiency is not limited to reducing the energy consumption,
   it is common to include carbon free, solar energy, wind energy,
   cogeneration in the efficiency.

   The type of the sources of energy of the power is one criteria of
   efficiency.

   There are other dimensions that must visible: As many telecom
   locations include battery or additionnally several backups levels (as
   example battery, standby generator ...) there is a requirement to
   known exactly when a backup power is in used and which one is.

2.3.4.  GREEN WG Charter Specifics

   Capture lifecycle energy data and integrate it with operational
   metrics.

2.3.5.  The Need for Energy Efficiency

   Considering energy from production to disposal supports the broader
   goal of reducing total environmental impact.

2.3.6.  Requirements for GREEN WG

   *  Awareness of backup systems (e.g., batteries, generators).

   *  Data ingestion from vendor databases or datasheets.

2.4.  Real-time Energy Metering of Virtualised or Cloud-native Network
      Functions

2.4.1.  Use Case Description

   Cloud-native and virtualized functions require precise real-time
   energy measurements to manage their dynamic workloads and
   infrastructure efficiently.  Effective metering of virtualized
   network infrastructure is critical for the efficient management and
   operation of next-generation mobile networks [GREEN_NGNM].

2.4.2.  GREEN WG Charter Specifics

   Meter and manage energy at both hardware and software layers.







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2.4.3.  The Need for Energy Efficiency

   Granular and real-time insights into energy use enable optimization
   of virtualized workloads, leading to reduced energy footprints.

2.4.4.  Requirements for GREEN WG

   // TODO.

2.5.  Indirect Energy Monitoring and control

2.5.1.  Use Case Description

   There are cases where Energy Management for some devices need to
   report on other entities.  There are two major reasons for this.

   o For monitoring energy consumption of a particular entity, it is not
   always sufficient to communicate only with that entity.  When the
   entity has no instrumentation for determining power, it might still
   be possible to obtain power values for the entity via communication
   with other entities in its power distribution tree.  A simple example
   of this would be the retrieval of power values from a power meter at
   the power line into the entity.  A Power Distribution Unit (PDU) and
   a Power over Ethernet (PoE) switch are common examples.  Both supply
   power to other entities at sockets or ports, respectively, and are
   often instrumented to measure power per socket or port.  Also it
   could be considered to obtain power values for the entity via
   communication with other entities outside of the power distribution
   tree, like for example external databases or even data sheets.

   o Similar considerations apply to controlling the power supply of an
   entity that often needs direct or indirect communications with
   another entity upstream in the power distribution tree.  Again, a PDU
   and a PoE switch are common examples, if they have the capability to
   switch power on or off at their sockets or ports, respectively.

2.5.2.  GREEN WG Charter Specifics

   inclusion of legacy or non-instrumented devices.

2.5.3.  The Need for Energy Efficiency

   Energy monitoring across the network, even for devices that lack
   built-in sensors.







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2.5.4.  Requirements for GREEN WG

   *  Indirect control mechanisms.

   *  Integration with external databases or datasheets.

2.6.  Consideration of other domains for obtention of end-to-end metrics

2.6.1.  Use Case Description

   The technologies under the scope of IETF provide the necessary
   connectivity to other technological domains.  For the obtention of
   metrics end-to-end it would be required to combine or compose the
   metrics per each of those domains.

   An exemplary case is the one of a network slice service.  The concept
   of network slice was initially defined by 3GPP [TS23.501], and it has
   been further extended to the concerns of IETF [RFC9543].

   In regards energy efficiency, 3GPP defines a number of energy-related
   key performance indicators (KPI) in [TS28.554], specifically Energy
   Efficiency (EE) and Energy Consumption (EC) KPIs.  There are KPIs
   particular for a slice supporting a specific kind of service (e.g.,
   Mobile Broadband or MBB), or generic ones, like Generic Network Slice
   EE or Network Slice EC.  Assuming these as the KPIs of interest, the
   motivation of this use case is the obtention of the equivalent KPIs
   at IETF level, that is, for the network slice service as defined in
   [RFC9543].

   Note that according to [TS28.554], the Generic Network Slice EE is
   the performance of the network slice divided by the Network Slice EC.
   Same approach can be followed at IETF level.  Note that for avoiding
   double counting the energy at IETF level in the calculation of the
   end-to-end metric, the 3GPP metric should only consider the
   efficiency and consumption of the 3GPP-related technologies.

2.6.2.  GREEN WG Charter Specifics

   cross-domain measurement alignment.

2.6.3.  The Need for Energy Efficiency

   Cross-domain energy visibility is essential for services spanning
   multiple infrastructure providers and technologies.







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2.6.4.  Requirements for GREEN WG

   *  Avoidance of double accounting.

   *  Metric mapping and transformation.

2.7.  Dynamic adjustment of network element throughput according to
      traffic levels in wireless transport networks

2.7.1.  Use Case Description

   Radio base stations are typically connected to the backbone network
   by means of fiber or wireless transport (e.g., microwave)
   technologies.  In the specific case of wireless transport, automation
   frameworks have been defined [ONF-MW][RFC8432][mWT025] for their
   control and management.

   One of the parameters subject of automated control is the power of
   the radio links.  The relevance of that capability is that the power
   can be adjusted accordingly to the traffic observed.  Wireless
   transport networks are typically planned to support the maximum
   traffic capacity in their area of aggregation, that is, the traffic
   peak.  With that input, the number of radio links in the network
   element and the corresponding power per radio link (for supporting a
   given modulation and link length in the worst weather conditions) are
   configured.  This is done to avoid any kind of traffic loss in the
   worst operational situation.  However, such operational needs are
   sporadic, giving room for optimization during normal operational
   circumstances and/or low traffic periods.

   Power-related parameters are for instance defined in [RFC8561].
   Those power parameters can be dynamically configured to adjust the
   power to the observed traffic levels with some coarse granularity,
   but pursuing certain degrees of proportionality.

2.7.2.  GREEN WG Charter Specifics

   This aligns with the GREEN WG goals of enabling dynamic and context-
   aware energy optimization at the transport layer.

2.7.3.  The Need for Energy Efficiency

   Wireless links configured for peak traffic are often underutilized,
   wasting energy.  Adjusting power to match demand can substantially
   reduce consumption.






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2.7.4.  Requirements for GREEN WG

   *  Adapt energy consumption to traffic change.

   *  Dynamic energy efficiency control and optimization.

2.8.  Video streaming use case

2.8.1.  Use Case Description

   Video streaming is nowadays the major source of traffic observed in
   ISP networks, in a propotion of 70% or even higher.  Over-the-top
   distribution of streaming traffic is typically done by delivering a
   unicast flow per end user for the content of its interest.In
   consequence, during the hours of higher demand, the total traffic in
   the network is proportional to the concurrence of users consuming the
   video streaming service.  The amount of traffic is also dependent of
   the resolution of the encoded video (the higher the resolution, the
   higher the bit rate per video flow), which tends to be higher as long
   as the users devices support such higher resolutions.

   The consequence of both the growth in the number of flows to be
   supported simultaneously, and the higher bit rate per flow, is that
   the nework elements in the path between the source of the video and
   the user have to be dimensioned accordingly.  This implies the
   continuous upgrade of those network elements in terms of capacity,
   with the need of deploying high-capacity network elements and
   components.  Apart from the fact that this process is shortening the
   lifetime of network elements, the need of high capacity interfaces
   also increase the energy consumption (despite the effort of
   manufacturers in creating more efficient network element platforms).
   Note that nowadays there is no actual possibility of activating
   energy consumption proportionality (in regards the delivered traffic)
   to such network elements.

   As a mean of slowing down this cycle of continuos renewal, and reduce
   the need og higher bit rate interfaces / line cards, it seems
   convenient to explore mechanisms that could reduce the volume of
   traffic without impacting the user service expectations.  Variants of
   multicast or different service delivery strategies can help to
   improve the energy efficiency associated to the video streaming
   service.  It should be noted that another front for optimization is
   the one related to the deployment of cache servers in the network.








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2.8.2.  GREEN WG Charter Specifics

   Video streaming represents a large portion of network traffic.
   Multicast techniques, adaptive streaming, and strategic caching can
   reduce traffic duplication and improve energy efficiency.

2.8.3.  The Need for Energy Efficiency

   Reducing redundant unicast traffic and improving caching strategies
   reduces backbone and access network energy consumption.

2.8.4.  Requirements for GREEN WG

   *  Support for multicast-aware energy metrics.

   *  Cache server placement optimization.

2.9.  WLAN Network Energy Saving

2.9.1.  Use Case Description

   In a WLAN network, Access Points(APs) are typically powered by Power
   over Ethernet (PoE) switches and represent a substantial portion of
   the energy consumed by edge network devices due to their high density
   and round-the-clock operation.

   This use case introduces a multi-mode approach for AP energy saving:
   The working status of the AP can be break down into 3 modes as
   follows: PoE power-off mode: In this mode, the PoE switch shuts down
   the port and stops supplying power to the AP.  The AP does not
   consume power at all.  When the AP wakes up, the port provides power
   again.  In this mode, it usually takes a few minutes for the AP to
   recover.  Hibernation mode: Only low power consumption is used to
   protect key hardware such as the CPU, and other components are shut
   down.  Low power consumption mode: Compared with the hibernation
   mode, the low power consumption mode maintains a certain
   communication capability.  For example, the AP retains only the 2.4
   GHz band and disables other radio bands.

   *  PoE Power-Off Mode: The PoE switch disables the port, completely
      cutting power to the AP.  No energy is consumed, though recovery
      takes several minutes when power is restored.

   *  Hibernation Mode: The AP powers down most components, preserving
      minimal CPU functionality to allow faster reactivation.






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   *  Low Power Mode: The AP disables some radios (e.g., 5GHz),
      retaining minimal operation (e.g., 2.4GHz) for reduced but
      persistent service.

   To maintain coverage and service quality, surrounding APs dynamically
   adjust their transmit power when some APs enter energy-saving states.
   Energy-saving schedules may be time-based (e.g., during off-hours) or
   traffic-aware (low utilization periods).

   Grouping APs by location enables coordinated energy-saving plans,
   minimizing disruption while maximizing cumulative energy reduction.

      /---\
     |     +-----+
     | AP  |     |
      \---/      |      +------------+
                 |      |            |
                 |------+     PoE    |
      /---\      |      |   Switch   |
     |     |     |      +------------+
     | AP  +-----+
      \---/

                        Figure 1: PoE Power Off Mode

                    4                         4
    +----------+   \|/        +----------+   \|/
    |          |    |         |          |    |
    |   +----+ |    |         |   +----+ |    |
    |   |5GHz+-+----+         |   |5GHz+-+-X--+
    |   | RF | |    2         |   | RF | |    2
    |   +----+ |   \|/    \   |   +----+ |   \|/
    |   +----+ |    |   ---\  |   +----+ |    |
    |  2.4GHz| |    |       \ |  2.4GHz| |    |
    |   | RF +-+----+       / |   | RF +-+-X--+
    |   +----+ |    2   ---/  |   +----+ |    2
    |   +----+ |   \|/    /   |   +----+ |   \|/
    |  2.4GHz| |    |         |  2.4GHz| |    |
    |   | RF |-+----+         |   | RF +-+----+
    |   +----+ |              |   +----+ |
    +----------+              +----------+

                    Figure 2: Low Power Consumption Mode








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        +--+  +--+    +--+
        |AP|--|AP|--- |AP|      ------------------------------
        +--+  +--+   \+--+      Grouping  Recommended
        /               \        Area     Energy Saving Period
     +--+     +--+      +--+    ------------------------------
     |AP|     |AP|      |AP|    XED01-1  01:00:00,06:30:00
     +--+     +--+      +--+
       |                 |      ------------------------------
        +--+          +--+
        |AP|  +--+   /|AP|      XED01-2  01:30:00,06:30:00
        +--+--|AP|--- +--+     --------------------------------
              +--+

               Figure 3: Wireless Resource Management on APs

2.9.2.  GREEN WG Charter Specifics

   This use case aligns with the GREEN WG's charter by:

   *  Illustrating real-world scenarios where energy efficiency
      mechanisms (discovery, monitoring, control) apply to IP-managed
      devices.

   *  Providing a localized but scalable use case that fits into broader
      energy-aware network management frameworks.

   -Addressing interoperability and observability across energy states
   and reporting mechanisms, including energy mix awareness.

2.9.3.  The Need for Energy Efficiency

   Given the number of deployed APs in enterprise and campus networks,
   their continuous operation contributes significantly to energy
   consumption.  Many of these environments experience well-defined
   periods of inactivity (e.g., nighttime, weekends), during which full
   AP operation is unnecessary.

   Reducing AP energy consumption during these periods, while
   maintaining sufficient coverage and quality of service, presents an
   effective opportunity for energy savings.  Applying coordinated
   power-state transitions across AP groups enables measurable
   improvements with minimal operational impact.

2.9.4.  Requirements for GREEN WG

   To support WLAN Network Energy Saving, the GREEN WG should consider:





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   *  Defining power state transition models and standard energy mode
      nomenclature for APs (e.g., OFF, HIBERNATE, LOW-POWER, ACTIVE).

   *  Specifying APIs or YANG models for monitoring and controlling AP
      power modes via PoE switches or WLAN controllers.

   *  Enabling reporting of per-mode energy consumption, transitions
      over time, and cumulative energy savings.

   *  Ensuring support for scheduled and dynamic (traffic-aware) control
      policies.

   *  Allowing integration with broader network monitoring frameworks
      for energy efficiency analysis at the local and network-wide
      level.

   *  Considering implications for resiliency, coverage trade-offs, and
      restart delays in power-off scenarios.

   Enable measuring and reporting of energy usage through metrics and
   attributes and allow operators to optimize energy usage.

2.9.5.  The Need for Energy Efficiency

   AP nodes as network devices with the largest number consume large
   amount of energy.

2.9.6.  Requirements for GREEN WG

   *  Energy saving mode switching based on network condition changes

   *  Allow network devices shutdown to save energy

   *  Allow working network devices transmit more power to increase the
      coverage of the entire area

2.10.  Fixed Network Energy Saving

2.10.1.  Use Case Description

   In many fixed networks, particularly those at metro or backbone
   level, traffic patterns follow a predictable tidal cycle - with
   clearly defined high-traffic and low-traffic periods.  These
   fluctuations provide opportunities for dynamic energy-saving
   mechanisms.  During low-traffic periods, certain network components
   can be deactivated or put into sleep mode.  Additionally, routers
   equipped with interfaces of varying speeds (e.g., from 1G to 400G)
   can dynamically adjust interface speeds, deactivate unused ports, or



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   scale down internal resources such as processor cores, chipset clock
   frequencies, or SerDes lanes, depending on traffic demand.

   In many fixed networks, particularly those at metro or backbone
   level, traffic patterns may follow a predictable tidal cycle - with
   clearly defined high-traffic and low-traffic periods, or may follow
   unbalanced traffic load - with clearly identified high-load and idle
   network elements.  These fluctuations provide opportunities for
   dynamic energy-saving mechanisms.  During low-traffic periods or
   unbalanced traffic load periods, the low traffic could be migrated
   and aggregated, certain network components can be deactivated or put
   into sleep mode.  Additionally, routers equipped with interfaces of
   varying speeds (e.g., from 1G to 400G) can periods dynamically adjust
   interface speeds, deactivate unused ports, or scale down internal
   resources such as processor cores, chipset clock frequencies, or
   SerDes lanes, depending on traffic demand.

2.10.2.  GREEN WG Charter Specifics

   The GREEN working group can contribute by defining standard
   mechanisms and protocols to: - Monitor traffic load in a standardized
   and interoperable manner. - Communicate energy-saving intents across
   network elements (e.g., turning off links or reducing interface
   speeds). - Signal state transitions (e.g., from active to low-power
   states) reliably, taking into account the need for fast reactivation
   during traffic bursts. - Ensure compatibility with QoS and network
   availability requirements.

2.10.3.  The Need for Energy Efficiency

   Network devices at metro or backbone network consume large amount of
   energy.

2.10.4.  Requirements for GREEN WG

   *  Standardized definitions and telemetry models for identifying
      tidal traffic patterns and low-utilization windows.

   *  Standardized AI/ML models for traffic prediction using historical
      data, capturing both long-term regularities and short-term bursts.

   *  Protocol support for energy-aware dynamic reconfiguration (e.g.,
      speed adjustment, core deactivation).

   *  Trade-offs between energy savings and network latency/performance.

   *  Mechanisms to synchronize energy-saving decisions across multiple
      devices (e.g., coordinated interface downshifts).



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   *  Fail-safe or fallback procedures to ensure robustness in case of
      unexpected traffic surges.

2.11.  Energy Efficiency Network Management

2.11.1.  Use Case Description

   Modern network operators need comprehensive visibility into the
   energy consumption and efficiency of their infrastructure.  This
   includes real-time and historical statistics of power usage per
   device, identification of devices participating in energy-saving
   modes, differentiation between energy-optimized and legacy devices,
   and aggregated views of energy trends across the entire network.
   Such visibility enables more informed decisions about network
   adjustments and optimizations that align with energy efficiency
   goals.

2.11.2.  GREEN WG Charter Specifics

   The GREEN WG has a role in developing interoperable models and
   mechanisms for: - Real-time telemetry and historical analysis of
   energy metrics. - Mapping energy efficiency indicators to network
   topology and traffic load. - Identifying energy-saving capabilities
   of devices (e.g., support for interface power scaling, sleep modes).
   - Integration with existing network management and orchestration
   systems. - Encouraging adoption of GREEN-compliant energy
   observability in vendor equipment.

2.11.3.  The Need for Energy Efficiency

   // TODO.

2.11.4.  Requirements for GREEN WG

   *  Standardized YANG models or data formats for energy metrics and
      efficiency reporting.

   *  Methods to correlate energy usage with traffic load and service
      demands.

   *  Interfaces for exposing energy capabilities and statuses of
      devices in a vendor-neutral way.

   *  Security and privacy implications of exposing energy-related
      telemetry.

   *  Guidelines for presenting energy insights to operators in a way
      that supports actionable decisions.



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2.12.  ISAC-enabled Energy-Aware Smart City Traffic Management

2.12.1.  Use case description

   Integrated Sensing and Communications (ISAC) is emerging as a key
   enabler for next-generation wireless networks, integrating sensing
   and communication functionalities within a unified system.  By
   leveraging the same spectral, hardware, and computational resources,
   ISAC enhances network efficiency while enabling new capabilities such
   as high-resolution environment perception, object detection, and
   situational awareness.  This paradigm shift is particularly relevant
   for applications requiring both reliable connectivity and precise
   sensing, such as autonomous vehicles, industrial automation, and
   smart city deployments.  Given its strategic importance, ISAC has
   gained significant traction in standardization efforts.  The ETSI
   Industry Specification Group (ISG) on ISAC has been established to
   explore technical requirements and use cases, while 3GPP has
   initiated discussions on ISAC-related features within its ongoing
   research on future 6G systems.  Furthermore, research initiatives
   within the IEEE and IETF are investigating how ISAC can be integrated
   into network architectures, spectrum management, and protocol design,
   making it a critical area of development in the evolution of wireless
   networks.

   This use case involves deploying ISAC systems in a smart city to
   monitor and optimize vehicles' traffic flows while minimizing energy
   consumption of the mobile network.  The system integrates sensing
   technologies, such as radar and LIDAR, with communication networks to
   detect vehicle density, monitor road conditions, and communicate with
   autonomous vehicles or traffic lights.  By using ISAC, the system
   minimizes redundant infrastructure (e.g., separate sensors and
   communication equipment), thus reducing the overall carbon and energy
   footprint.

   On the other hand, such an infrastructure will have to adapt its
   energy optimization policies to sensing applications: critical
   functions (e.g., threat detection) must run continuously, while
   others should activate depending on the context.

2.12.2.  GREEN WG Specifics

   Energy Consumption Monitoring: Each ISAC component (e.g., roadside
   units, integrated sensors, and communication transceivers) is capable
   of reporting its energy consumption in real time to the centralized
   or distributed energy management system.






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   Reconfiguration for Energy Efficiency: The system can dynamically
   switch between high-resolution sensing modes (e.g., during peak
   hours) and low-power modes (e.g., during low traffic periods).  The
   network can reconfigure traffic communication paths to prioritize
   routes or nodes that consume less power, leveraging energy-efficient
   communication protocols.

   Integration of Local and Global Energy Goals: The system can operate
   both locally (e.g., turning off specific roadside units in low-
   traffic areas) and globally (e.g., modifying traffic patterns across
   the city) to achieve defined energy consumption goals.

2.12.3.  Requirements for GREEN WG

   1.  Measurement Granularity:

   *  Ability to measure energy consumption per ISAC component (e.g.,
      roadside unit, sensor, transceiver).

   *  Granular reporting per communication link or sensing mode (e.g.,
      high-power radar mode vs. low-power mode).

   1.  Power Control Mechanisms:

   *  Ability to switch components on/off or place them in sleep/standby
      mode when not in use.

   *  Support for dynamic adjustment of sensing resolution or
      communication bandwidth to balance energy savings and system
      performance.

   1.  Reconfiguration and Adaptability:

   *  Support for hardware reconfiguration (e.g., adaptive sensing
      modes, transceiver settings) to optimize energy use.

   *  Mechanisms to steer traffic or adjust network routing based on
      global or local energy-saving objectives.

   1.  Global Coordination:

   *  Capabilities for cross-domain coordination to enable global
      optimization (e.g., city-wide traffic rerouting or dynamic
      resource allocation across different regions).

   *  Ability to aggregate and analyze energy consumption data from all
      ISAC components to inform high-level decision-making.




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   1.  Energy-Aware Standards and Protocols:

       *  Communication protocols that minimize power usage while
          maintaining reliability.

       *  Interoperability standards for energy-aware reconfiguration
          across heterogeneous ISAC components and systems.

2.13.  Double Accounting Open issue

2.13.1.  Use case description

   Energy consumption monitoring often includes metering at both
   upstream and downstream levels of power distribution.  While this can
   provide granular visibility, it may also lead to double accounting if
   not carefully managed.

   A common case arises when energy is measured at the input of a Power
   Delivery Unit (PDU), and individually at each device powered by that
   PDU (e.g., servers, switches).  Since the PDU input already reflects
   the downstream consumption, summing the per-device values with the
   PDU input results in redundant reporting.  A similar issue occurs
   with Power over Ethernet (PoE) infrastructures when a network switch
   supply power directly to devices.  If the total power consumption
   measured encompasses both the power delivered to the PoE switch and
   to the powered devices, this again results in double accounting.

   These 2 cases distort energy dashboards and indicators such as Power
   Usage Effectiveness (PUE).

2.13.2.  GREEN WG Charter Specifics

   Unlike most of the WGs, the GREEN WG purpose sums the constraints of
   data networks and grid/off-grid networks, independantly of the
   location of the network domain in the architecture (aka edge,
   core...): - include the grid network picture in networks operation

2.13.3.  The Need for Energy Efficiency

   // TODO.

2.13.4.  Requirements for GREEN WG

   The monitoring must not count twice the power that passthru devices
   and components monitored, including legacy elements.

2.14.  Energy Efficiency Under Power Shortage




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2.14.1.  Use case description

   This use case focuses on network devices (e.g., routers, switches,
   access points) that must maintain essential connectivity during power
   shortages.  Telecom locations use different power backups levels (as
   example battery, standby generator ...).  Devices may have access to
   one or more backup power sources such as onboard batteries, PoE
   fallback, or centralized UPS systems.  When a power shortage occurs,
   the network device transitions from grid power to available backup
   sources and must prioritize operational resilience over typical
   energy optimization strategies.  Unlike behavior in a normally
   powered state, the focus here is not on minimizing energy consumption
   per se, but on sustaining essential operation with limited energy and
   prepare to worse situations and more constrained powered state
   fallbacks.  These behaviors increase the device's ability to operate
   longer under backup power, ensuring availability of essential
   services during outages.

   Data networks and grid networks resiliency are closely interleaved
   during power shortage.  It is a race between the speed of the
   operations to restore the grid network and the availability of mobile
   connectivity for power grid repair teams because of the impairment of
   operational visibility and response coordination.

   Network constraints differ in sparse or dense situations but shortage
   impacts change accordingly.  This is becoming crucial and not limited
   to sparse environments where stable power supply is well known to not
   be guaranteed: it applies to dense cities' utilities which operations
   are coupled to the simoultaneous availability of both power and
   persistent data communication and compute at the edge.

2.14.2.  GREEN WG Charter Specifics

   Unlike most of the WGs, the GREEN WG purpose sums the constraints of
   data networks and grid/off-grid networks, independantly of the
   location of the network domain in the architecture (aka edge,
   core...): - Improved networks resiliency by making energy constraints
   an input into the network's operations.

2.14.3.  The Need for Energy Efficiency

   Energy efficiency under power shortage conditions is fundamentally
   different from routine energy optimization.  In this context, energy
   is a finite and rapidly depleting resource, not just an environmental
   concern or cost factor: - Optimize backup power usage for resilience
   - Maintain critical networking capabilities during power shortage
   events - Maximize operational uptime using fallback power sources




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2.14.4.  Requirements for GREEN WG

   *  Awareness of backup systems (e.g., batteries, generators).

   *  Awareness of hierarchical fallback to more constrained powered
      state.

2.15.  Energy-Efficient Management of Distributed AI Training Workloads

2.15.1.  Use Case Description

   Training large AI models requires distributed computing across
   multiple servers or GPUs.  This distributed training generates
   significant East-West traffic as data is exchanged between nodes.
   This use case focuses on managing the energy consumption of
   distributed AI training workloads by optimizing data placement,
   communication patterns, and compute resource allocation.  Strategies
   include scheduling training jobs to run during periods of lower
   energy prices, using compression techniques to reduce data transfer
   volume, and dynamically adjusting the number of active nodes based on
   training progress.  It is also critical to have a cross-domain view
   of the end to end flow to address power consumption holistically.

2.15.2.  GREEN WG Charter Specifics

   This use case contributes to the GREEN WG's goals by addressing the
   energy efficiency of emerging workloads and exploring the use of
   dynamic resource allocation to minimize energy consumption.  It calls
   for energy-aware scheduling and optimization techniques.

2.15.3.  The Need for Energy Efficiency

   AI training is a computationally intensive task that consumes a
   significant amount of energy.  Optimizing the energy efficiency of
   distributed AI training workloads can reduce costs, improve
   sustainability, and enable more widespread adoption of AI
   technologies.  There is an impact not only for the network
   consumption, rather than the compute consumption.

2.15.4.  Requirements for GREEN WG

   *  East-West Traffic Monitoring: Standardized mechanisms for
      monitoring the volume, type, and characteristics of East-West
      traffic.

   *  Workload Characterization: Standardized methods for characterizing
      the energy consumption profile of AI training workloads.




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   *  Energy-Aware Scheduling: APIs for scheduling training jobs based
      on energy prices, grid conditions, and other energy-related
      factors.

   *  Data Compression and Optimization: Techniques for reducing the
      volume of data transferred during distributed training.

   *  Dynamic Resource Allocation: Mechanisms for dynamically adjusting
      the number of active nodes based on training progress and energy
      availability.

   *  Resource co-location, so the data used for processing can be as
      close as possible to the data crunching machines.

2.16.  Network-level Cross Layer Energy Saving

2.16.1.  Use Case Description

   For the carrier of integrated services (e.g., TDM/IP) using physical
   infrastructures like optical fiber and optical wavelengths, the
   transport network functions as the underlay to the IP network as the
   overlay.  Here the transport network is designed for guaranteed
   connectivity, with relatively rigid resource allocation while the IP
   network supports flexible traffic on runtime. the technology
   difference creates the challenge of "dynamic traffic vs. static
   infrastructure".  In the section 2.10, fixed network energy saving
   use case describes that during low-traffic periods or unbalanced
   traffic load periods, certain network components can be deactivated
   or put into sleep mode.  Imagine when an IP line card is shutdown, it
   not only affects the link in the overlying IP layer (L3) but also the
   link in the transport layer (L0/L1/L2), network-level cross-layer
   energy saving management can enable a holistic optimization of
   resources across layers while ensuring the overall service QoS.  This
   allows some resources across layers to enter a sleep or lower-power
   state, thereby reducing overall energy consumption.

2.16.2.  GREEN WG Charter Specifics

   *  Multi-layer energy management: This use case highlights the
      interaction between the transport network underlay (L0-L2) and the
      IP overlay (L3).  The GREEN WG can define how energy-saving
      actions are safely coordinated across layers to maintain service
      continuity, which is a critical aspect of cross-layer
      optimization.







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2.16.3.  The Need for Energy Efficiency

   When talking about network-level energy saving, It's inevitable to
   face the challenge of "dynamic traffic vs. static infrastructure" and
   deal with different network layers.

2.16.4.  Requirements for GREEN WG

   *  Mechanisms to coordinate energy-saving decisions across multiple
      layers(e.g., coordination between IP layer and Transport layer).

3.  Security Considerations

   Energy efficiency management comes with numerous security
   considerations :

   Controlling Power State and power supply of entities are considered
   highly sensitive actions, since they can significantly affect the
   operation of directly and indirectly connected devices.  Therefore,
   all control actions must be sufficiently protected through
   authentication, authorization, and integrity protection mechanisms.

   Entities that are not sufficiently secure to operate directly on the
   public Internet do exist and can be a significant cause of risk, for
   example, if the remote control functions can be exercised on those
   devices from anywhere on the Internet.

   The monitoring of energy-related quantities of an entity as addressed
   can be used to derive more information than just the received and
   provided energy; therefore, monitored data requires protection.  This
   protection includes authentication and authorization of entities
   requesting access to monitored data as well as confidentiality
   protection during transmission of monitored data.  Privacy of stored
   data in an entity must be taken into account.  Monitored data may be
   used as input to control, accounting, and other actions, so integrity
   of transmitted information and authentication of the origin may be
   needed.

4.  IANA Considerations

   This document has no IANA actions.










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5.  Acknowledgments

   The contribution of Luis M.  Contreras to this document has been
   supported by the Smart Networks and Services Joint Undertaking (SNS
   JU) under the European Union's Horizon Europe research and innovation
   projects 6Green (Grant Agreement no. 101096925) and Exigence (Grant
   Agreement no. 101139120).

6.  Use Cases Living List

   Consider 5g vs network slicing: 3GPP spec describing energy
   efficiency KPIs. 3GPP TS 28.554.
   Reference:https://datatracker.ietf.org/doc/rfc9543/ Connectivity from
   radio side (trying to control the traffic/related work to CCAMP)
   Marisol to add one use case: drift from data specifications...
   (somehow link to the above) Energy Metric in E2E view

7.  References

7.1.  Normative References

   [IEC.61850-7-4] International Electrotechnical Commission,
   "Communication networks and systems for power utility automation --
   Part 7-4: Basic communication structure -- Compatible logical node
   classes and data object classes", March 2010.

   [IEC.62053-21] International Electrotechnical Commission,
   "Electricity metering equipment (a.c.) -- Particular requirements --
   Part 21: Static meters for active energy (classes 1 and 2)", January
   2003.

   [IEC.62053-22] International Electrotechnical Commission,
   "Electricity metering equipment (a.c.) -- Particular requirements --
   Part 22: Static meters for active energy (classes 0,2 S and 0,5 S)",
   January 2003.

   [ATIS-0600015.03.2013] ATIS, "ATIS-0600015.03.2013: Energy Efficiency
   for Telecommunication Equipment: Methodology for Measurement and
   Reporting for Router and Ethernet Switch Products", 2013.

7.2.  Informative References

   [IEC.60050] International Electrotechnical Commission, "Electropedia:
   The World's Online Electrotechnical Vocabulary", 2013,
   http://www.electropedia.org/iev/iev.nsf/welcome?openform
   (http://www.electropedia.org/iev/iev.nsf/welcome?openform).





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8.  Appendix I: Template preparation

   This appendix should be removed when the template will be stable.

   It is based on the example from https://datatracker.ietf.org/doc/
   rfc9450/.

8.1.  Use Case Description

   General description of the use case.

8.2.  GREEN WG Charter Specifics

   (if there are no GREEN specific aspects, then it is not a UC to be
   documented) For example, the use case involves components that can
   report on energy consumption and that might be reconfigured (on a
   local or global scale) to operate based on energy goals/limitations.

8.2.1.  The Need for Energy Efficiency

8.3.  Requirements for GREEN

   Examples (can be split into different categories to facilitate a
   summary at the end of the document):

   *  Granularity of measurements should be per component, per line, per
      port.

   *  Ability to switch on/off, put on sleep mode' components.

   *  Ability to reconfigure hardware mode based on power savings (e.g.,
      reduce reliability or speed).

   *  Ability to operate globally (not constrained to just one device)
      based on power savings/goals (e.g., steer traffic using a
      different path that consumes less energy).















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  (a)              (b)              (c)
  Inventory        Monitor       +- DataSheets/DataBase and/or via API
  Of identity      Energy        |  Metadata and other device/component
  and Capability   Efficiency    |  /network related information:
       ^               ^         |
       |               |         |  .Power/Energy related metrics
       |               |         |  .information
       |               |         |  .origin of Energy Mix
       |               |         |  .carbon aware based on location
       |               |         |
       |               |         |
       |               |         |
       |               |         v
  +--------------------------------------------------------------------+
  |                   *                                                |
  |     (2) controller   (collection, compute and aggregate?)          |
  |                                                                    |
  +--------------------------------------------------------------------+
               ^              ^                   ^ |
    (d)        |  (e)         |  (f)              | |(g)
    Inventory  |  Monitor     |  GREEN WG:        | |GREEN WG: Control
    Capability |  Traffic     |  Monitor power    | |(Energy saving
               |  & power     |  Proportion,      | |Functionality
               |  consumption |  Energy efficiency| |Localized mgmt/
               |              |  ratio, etc)      | |network wide mgmt)
               |              |                   | |
               |              |                   | |
               |              |                   | v
  +--------------------------------------------------------------------+
  |                                            *                       |
  |                  (1) Device/Component Level                        |
  |                                                                    |
  | +---------+  +-----------+  +----------------+  +----------------+ |
  | | (I)     |  | (II)      |  | (III)          |  | (IV)           | |
  | | Network |  | Device    |  | Legacy Network |  | 'Attached'(PoE | |
  | | Device  |  | Component |  | Device         |  | kind) Device   | |
  | |         |  |           |  |                |  |                | |
  | +---------+  +-----------+  +----------------+  +----------------+ |
  +--------------------------------------------------------------------+

  (*) Energy Efficiency Management Function is implemented inside the
  device or in a controller

               Figure 4: Framework discussed during the BoF

   The main elements in the framework are as follows:

   (a),(d) Discovery and Inventory



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   (b),(c) GREEN Metrics

   (b),(f) Monitor energy efficiency

   (e) Monitor power consumption and traffic (IPPM WG throughput,
   traffic load, etc)

   (g) Control Energy Saving

9.  Appendix II: Necessity and Impact of a Framework for Energy
    Efficiency Management

   This appendix outlines the necessity of defining a framework for
   energy efficiency management within the GREEN Working Group's current
   phase.  Establishing a framework now is crucial for standardizing
   processes, optimizing energy usage, and ensuring interoperability
   across network devices.  Immediate action enables the industry to
   achieve cost savings, meet regulatory requirements, and maintain
   competitiveness.  By utilizing insights from existing use cases, the
   framework can deliver actionable metrics and support ongoing
   innovation, positioning the industry to effectively manage future
   energy challenges.

9.1.  Framework Necessity

   Analyzing use cases such as the "Incremental Application of the GREEN
   Framework" reveals the critical need for a structured approach to
   transitioning network devices towards energy-efficient operations.
   The framework is essential for:

   *  *Standardization*: Ensuring consistent practices across different
      devices and network segments to facilitate interoperability.

   *  *Efficient Energy Management*: Providing guidelines to identify
      inefficiencies and implement improvements.

   *  *Scalability*: Offering solutions that accommodate growing network
      demands and complexity.

   *  *Cost Reduction*: Optimizing energy usage to lower operational
      costs and extend equipment lifecycles.

   *  *Competitiveness*: Enabling organizations to maintain a
      competitive edge through enhanced sustainability.

   *  *Environmental Impact*: Supporting broader sustainability
      initiatives by reducing carbon footprints.




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   *  *Simplified Implementation*: Streamlining the deployment of
      energy-efficient measures to minimize service disruptions.

   *  *Security*: Protecting sensitive operations related to power
      states and consumption.

9.2.  Use Cases Calling for a Framework

   Multiple use cases underscore the need for a framework, including:

   *  *Incremental Application of the GREEN Framework*

   *  *Selective Reduction of Energy Consumption in Network Parts*

   *  *Real-time Energy Metering of Virtualized or Cloud-native Network
      Functions*

   *  *Indirect Energy Monitoring and Control*

   *  *Consideration of Other Domains for Obtention of End-to-End
      Metrics*

   *  *Dynamic Adjustment of Network Element Throughput*

   *  *Video Streaming Use Case*

   *  *WLAN Network Energy Saving*

   *  *Fixed Network Energy Saving*

   *  *Energy Efficiency Network Management*

   These use cases highlight diverse aspects of energy management that
   require a cohesive framework for effective implementation.

9.3.  Impact on Energy Metrics

   The framework will significantly enhance the creation of energy
   metrics with actionable insights by:

   *  *Standardizing Metrics*: Establishing consistent measurement
      protocols for energy consumption and efficiency.

   *  *Enhancing Data Collection*: Facilitating comprehensive monitoring
      and data aggregation across devices.

   *  *Supporting Real-time Monitoring*: Enabling dynamic tracking and
      immediate optimization of energy usage.



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   *  *Integration Across Devices*: Ensuring interoperability for
      network-wide data analysis.

   *  *Providing Actionable Insights*: Translating raw data into
      meaningful information for decision-making.

9.4.  Current Device Readiness

   While many modern networking devices have basic energy monitoring
   capabilities, these are often proprietary.  The framework will define
   requirements to enhance these capabilities, enabling standardized
   metric production and meaningful data contributions for energy
   management goals.

9.5.  Why Now?

   The decision to define the framework now, rather than later, is
   driven by:

   *  *Immediate Benefits*: Start realizing cost savings, reduced carbon
      footprints, and improved efficiencies.

   *  *Rapid Technological Advancements*: Aligning the framework with
      current technologies to prevent obsolescence.

   *  *Increasing Energy Demands*: Mitigating the impact of growing
      energy consumption on costs and sustainability.

   *  *Regulatory Pressure*: Preparing for compliance with existing and
      anticipated sustainability regulations.

   *  *Competitive Advantage*: Positioning organizations as leaders in
      sustainability and innovation.

   *  *Foundational Work Ready*: Building on the use cases and
      requirements established in Phase I.

   *  *Proactive Risk Management*: Minimizing risks associated with
      energy costs and environmental factors.

   *  *Facilitate Future Innovations*: Creating a platform for
      continuous improvements and adaptations.

   *  *Stakeholder Engagement*: Ensuring diverse perspectives are
      reflected for broader adoption.






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   In conclusion, establishing the framework for energy efficiency
   management now is strategic and timely, leveraging the current
   momentum of use cases and requirements to drive meaningful progress
   in energy efficiency management.  Delaying its development could
   result in missed opportunities for immediate benefits, increased
   costs, and challenges in adapting to future technological and
   regulatory landscapes.

10.  Informative References

   [GREEN_NGNM]
              "NGMN Alliance, GREEN FUTURE NETWORKS: METERING IN
              VIRTUALISED RAN INFRASTRUCTURE", n.d.,
              <https://www.ngmn.org/publications/metering-in-
              virtualised-ran-infrastructure.html>.

   [legacy-path]
              "Requirements for Energy Efficiency Management", 21 July
              2024, <https://datatracker.ietf.org/doc/draft-stephan-
              legacy-path-eco-design>.

   [mWT025]   "ETSI GR mWT 025, Wireless Backhaul Network and Services
              Automation: SDN SBI YANG models, V1.1.1.", 31 March 2021.

   [ONF-MW]   "ONF TR-532, Microwave Information Model, version 2.0.",
              31 January 2024.

   [RFC8432]  Ahlberg, J., Ed., Ye, M., Ed., Li, X., Contreras, LM., and
              CJ. Bernardos, "A Framework for Management and Control of
              Microwave and Millimeter Wave Interface Parameters",
              RFC 8432, DOI 10.17487/RFC8432, October 2018,
              <https://www.rfc-editor.org/rfc/rfc8432>.

   [RFC8561]  Ahlberg, J., Ye, M., Li, X., Spreafico, D., and M.
              Vaupotic, "A YANG Data Model for Microwave Radio Link",
              RFC 8561, DOI 10.17487/RFC8561, June 2019,
              <https://www.rfc-editor.org/rfc/rfc8561>.

   [RFC9543]  Farrel, A., Ed., Drake, J., Ed., Rokui, R., Homma, S.,
              Makhijani, K., Contreras, L., and J. Tantsura, "A
              Framework for Network Slices in Networks Built from IETF
              Technologies", RFC 9543, DOI 10.17487/RFC9543, March 2024,
              <https://www.rfc-editor.org/rfc/rfc9543>.

   [TS23.501] "3GPP TS 23.501, System architecture for the 5G System
              (5GS), 17.6.0.", 22 September 2022.





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   [TS28.554] "3GPP TS 28.554, Management and orchestration; 5G end to
              end Key Performance Indicators (KPI), 17.15.0.", 25
              September 2024.

Authors' Addresses

   Emile Stephan
   Orange
   Email: emile.stephan@orange.com


   Marisol Palmero
   Individual
   Email: marisol.ietf@gmail.com


   Benoit Claise
   Huawei
   Email: benoit.claise@huawei.com


   Qin Wu
   Huawei
   Email: bill.wu@huawei.com


   Luis M. Contreras
   Telefonica
   Email: luismiguel.contrerasmurillo@telefonica.com


   Carlos J. Bernardos
   Universidad Carlos III de Madrid
   Email: cjbc@it.uc3m.es


   Xinyu Chen
   China Mobile
   Email: chenxinyu@chinamobile.com












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