Getting Ready for Energy-Efficient Networking E. Stephan
Internet-Draft Orange
Intended status: Informational M. Palmero
Expires: 17 November 2025 Cisco Systems, Inc.
B. Claise
Q. Wu
Huawei
L. M. Contreras
Telefonica
C. J. Bernardos
Universidad Carlos III de Madrid
16 May 2025
Use Cases for Energy Efficiency Management
draft-stephan-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-stephan-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-stephan-green-use-cases/draft-
stephan-green-use-cases.html. Status information for this document
may be found at https://datatracker.ietf.org/doc/draft-stephan-green-
use-cases/.
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(mailto:green@ietf.org), which is archived at
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Source for this draft and an issue tracker can be found at
https://github.com/emile22/draft-stephan-green-use-cases.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1. Incremental Application of the GREEN Framework . . . . . 4
2.2. Selective reduction of energy consumption in network parts
proportional to traffic levels . . . . . . . . . . . . . 5
2.3. Reporting on Lifecycle Management . . . . . . . . . . . . 6
2.3.1. Carbon Reporting . . . . . . . . . . . . . . . . . . 6
2.3.2. Energy Mix . . . . . . . . . . . . . . . . . . . . . 6
2.4. Real-time Energy Metering of Virtualised or Cloud-native
Network Functions . . . . . . . . . . . . . . . . . . . 6
2.5. Indirect Energy Monitoring and control . . . . . . . . . 7
2.6. Consideration of other domains for obtention of end-to-end
metrics . . . . . . . . . . . . . . . . . . . . . . . . 7
2.7. Dynamic adjustment of network element throughput according
to traffic levels in wireless transport networks . . . . 8
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2.8. Video streaming use case . . . . . . . . . . . . . . . . 8
2.9. WLAN Network Energy Saving . . . . . . . . . . . . . . . 9
2.10. Fixed Network Energy Saving . . . . . . . . . . . . . . . 11
2.11. Energy Efficiency Network Management . . . . . . . . . . 11
2.12. ISAC-enabled Energy-Aware Smart City Traffic
Management . . . . . . . . . . . . . . . . . . . . . . . 11
2.12.1. Use case description . . . . . . . . . . . . . . . . 11
2.12.2. GREEN Specifics . . . . . . . . . . . . . . . . . . 12
2.12.3. Requirements for GREEN . . . . . . . . . . . . . . . 12
2.13. Double Accounting Open issue . . . . . . . . . . . . . . 13
3. Security Considerations . . . . . . . . . . . . . . . . . . . 14
4. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
5. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 14
6. Use Cases Living List . . . . . . . . . . . . . . . . . . . . 15
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 15
7.1. Normative References . . . . . . . . . . . . . . . . . . 15
7.2. Informative References . . . . . . . . . . . . . . . . . 16
8. Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . 16
9. Informative References . . . . . . . . . . . . . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 17
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.
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2.1. Incremental Application of the GREEN Framework
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 the move one started;
Once upon a time there was an very old legacy router named Rusty
equipped with outdated ethernet and ugly optical interfaces. Despite
his worn-out appearance, Rusty was determined to contribute to the
energy efficiency effort. He dreamed of finding a way to optimize
his old circuits and help reduce the power consumption of the network
he had faithfully served for so many years. Though he was no longer
in his prime, Rusty believed that even an old router like him could
make a difference in a world striving for sustainability and help
reduce the carbon footprint. He is convince that he still had a part
to play in making the digital world a greener place.
Device moving gradually to GREEN energy efficiency support:
* 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.
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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.
* step 3 "device controleur"
* step 4 "network level"
(i) Avoid a power-on/power-off frequency to break component parts
(aka laser, power parts, wire connectors ...)
(ii) the gain must be measurable
(iii) network-wide energy efficiency solutions must include legacy
devices and green-wg ready devices
2.2. Selective reduction of energy consumption in network parts
proportional to traffic levels
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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2.3. Reporting on Lifecycle Management
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.
2.3.1. 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.
2.3.2. 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.
2.4. Real-time Energy Metering of Virtualised or Cloud-native Network
Functions
Facilitating more precise and real-time estimations of energy
consumed by virtualised or cloud-native network functions.
Effective metering of virtualized network infrastructure is critical
for the efficient management and operation of next-generation mobile
networks [GREEN_NGNM].
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2.5. Indirect Energy Monitoring and control
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.
2.6. Consideration of other domains for obtention of end-to-end metrics
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].
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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.
2.7. Dynamic adjustment of network element throughput according to
traffic levels in wireless transport networks
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.
2.8. Video streaming use case
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.
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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.
2.9. WLAN Network Energy Saving
In a WLAN network, The AP is usually powered by a PoE switch. AP
nodes are network devices with the largest number and consuming most
of energy. Therefore, the working status of the AP is the core of
the energy saving solution.
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.
In energy saving deployment, after the surrounding energy saving APs
are shut down, the Working AP automatically adjusts their transmit
power to increase the coverage of the entire area at specific energy
saving period. In such case, energy saving APs can freely choose to
switch to any mode we described above.
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/---\
| +-----+
| 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
+--+ +--+ +--+
|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
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2.10. Fixed Network Energy Saving
Traffic on the Tidal network has an obvious tidal period, including
heavy-traffic periods and light-traffic periods: The time duration of
heavy traffic load and light traffic load are clearly distinguished.
The switching time between the heavy-traffic period and the light-
traffic period is quite fixed and cyclic. In a tidal network, some
network devices can be shut down or sleep during low-traffic periods
to save energy. In the metro or backbone network, the routers
support various different speed interfaces, e.g., the gigabit level
to 10GE/50GE, or 100G to 400G. Routers might choose to adjust speed
of the interface or downgrade from high speed interface to low speed
interface based on network traffic load changes to save the energy.
In addition, the routers can adjust the number of working network
processor cores and clock frequency of chipsets and the number of
SerDes buses based on network traffic load changes to save the
energy.
2.11. Energy Efficiency Network Management
Network level Energy Efficiency allows network operators not only see
real time energy consumption in the network devices of large scale
network, but also allow you see o which network devices enable energy
saving, which devices not,which are legacy ones, o The total energy
consumption changing trend over the time of the day, for all network
devices, o Energy efficiency changing trend over the time of the day
for the whole network. With the better observability to energy
consumption statistics data and energy efficiency statistics data,
the network operators can know which part of the network need to be
adjusted or optimized based on network status change.
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
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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.
2.12.2. GREEN 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.
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
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:
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* 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.
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
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.
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These 2 cases distort energy dashboards and indicators such as Power
Usage Effectiveness (PUE).
3. Security Considerations
Resiliency is an implicit use case of energy efficiency management
which 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.
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).
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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.
[IEEE-100] IEEE, "The Authoritative Dictionary of IEEE Standards
Terms, IEEE 100, Seventh Edition", December 2000.
[IEEE-1621] Institute of Electrical and Electronics Engineers, "IEEE
1621-2004 - IEEE Standard for User Interface Elements in Power
Control of Electronic Devices Employed in Office/Consumer
Environments", 2004.
[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.
[ETSI-ES-203-136] ETSI, "ETSI ES 203 136: Environmental Engineering
(EE); Measurement methods for energy efficiency of router and switch
equipment", 2017, <https://www.etsi.org/deliver/
etsi_es/203100_203199/203136/01.02.00_50/ es_203136v010200m.pdf>.
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[ITUT-L.1310] ITU-T, "L.1310 : Energy efficiency metrics and
measurement methods for telecommunication equipment", 2020,
https://www.itu.int/rec/T-REC-L.1310/en (https://www.itu.int/rec/T-
REC-L.1310/en).
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).
[ITU-M.3400] International Telecommunication Union, "ITU-T
Recommendation M.3400 -- Series M: TMN and Network Maintenance:
International Transmission Systems, Telephone Circuits, Telegraphy,
Facsimile and Leased Circuits -- Telecommunications Management
Network - TMN management functions", February 2000.
8. Appendix
This appendix should be removed when the initial set of GREEN WG
documents will be stable
9. Informative References
[GREEN-BOF]
"BOF proposal for GREEN WG Creation", 10 May 2024,
<https://github.com/marisolpalmero/GREEN-bof>.
[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.
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[operators-inputs]
"Input from Operators to GREEN BoF", 20 July 2024,
<https://datatracker.ietf.org/meeting/120/materials/
slides-120-green-input-from-operators-to-green-bof-01>.
[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>.
[sustainability-insights]
"Sustainability Insights", 7 May 2024,
<https://datatracker.ietf.org/doc/html/draft-almprs-
sustainability-insights>.
[TS23.501] "3GPP TS 23.501, System architecture for the 5G System
(5GS), 17.6.0.", 22 September 2022.
[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
Cisco Systems, Inc.
Email: mpalmero@cisco.com
Benoit Claise
Huawei
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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
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