Proposed Sustainability and the Internet Proposed Research GroupA. Gallego Sanchez
Internet-Draft Deutsche Telekom
Intended status: Informational A. Rodriguez-Natal
Expires: 30 August 2026 Cisco
L. M. Contreras
Telefonica
M. Palmero
J. Lindblad
All For Eco
February 2026
Sustainability holistic API for Path Energy Evaluation (SHAPE)
draft-amalj-sustain-shape-00
Abstract
This document describes an API to query a network regarding its
Energy Traffic Ratio and other sustainability-related metrics for a
given network path.
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://galledohm.github.io/draft-amalj-sustain-shape/draft-amalj-
sustain-shape.html. Status information for this document may be
found at https://datatracker.ietf.org/doc/draft-amalj-sustain-shape/.
Discussion of this document takes place on the Proposed
Sustainability and the Internet Proposed Research Group Research
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https://www.ietf.org/mailman/listinfo/sustain/.
Source for this draft and an issue tracker can be found at
https://github.com/galledohm/draft-amalj-sustain-shape.
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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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
and restrictions with respect to this document.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Conventions and Definitions . . . . . . . . . . . . . . . . . 3
3. Sustainability holistic API for Path Energy Evaluation
(SHAPE) . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1. Energy Information . . . . . . . . . . . . . . . . . . . 4
3.2. Recursive Usage . . . . . . . . . . . . . . . . . . . . . 6
4. YANG Module . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.1. Module Structure . . . . . . . . . . . . . . . . . . . . 8
4.2. Module Definition . . . . . . . . . . . . . . . . . . . . 8
5. Security Considerations . . . . . . . . . . . . . . . . . . . 15
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 16
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 16
7.1. Normative References . . . . . . . . . . . . . . . . . . 17
7.2. Informative References . . . . . . . . . . . . . . . . . 18
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 19
Appendix A. Use Cases . . . . . . . . . . . . . . . . . . . . . 19
A.1. SD-WAN . . . . . . . . . . . . . . . . . . . . . . . . . 19
A.2. Multilayer Energy Management . . . . . . . . . . . . . . 20
A.3. SLA Negotiation for Green Services . . . . . . . . . . . 20
Appendix B. Requirements for Energy Efficiency Management . . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 23
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1. Introduction
Sustainability is becoming one of the major societal goals for the
next decade, and networks are one of the major consumers of energy
nowadays. Sustainability of network services is thus one of the
forefronts of innovation and action from network service
stakeholders, involving manufacturers, operators and customers. In
this line, there is a shared goal of achieving better energy and
carbon awareness.
As with any other network metric, the energy traffic ratio could be
collected from the underlying network infrastructure. However, there
is not a common or single definition of energy and sustainability
metrics towards network consumers so that they can be uniformly
reported, particularly in heterogeneous network scenarios. This
document introduces an API to query networks about the Energy Traffic
Ratio.
Beyond simple efficiency indicators such as watts per gigabit,
network stakeholders are increasingly interested in richer
sustainability information, such as carbon intensity, energy mix,
power usage effectiveness (PUE), idle energy draw, transmission
losses, and cooling overheads (e.g., Cooling Energy Ratio). In
addition, operational and temporal aspects matter: the ability of a
path to spend time in low-power states (Sleep-mode Availability), the
variability of carbon intensity over time (Temporal Carbon
Variability), and the stability of reported sustainability behavior
(e.g., Sustainability Stability Index).
Finally, sustainability data is increasingly used for automated
decision-making and assurance (e.g., in green SLAs), which introduces
a need for indicators of data quality and robustness. Metrics such
as variance of energy consumption (VEC), anomaly detection signals
(e.g., Anomaly Factor), and a trustworthiness score of data sources
(TDS) help distinguish persistent characteristics from transient
conditions and support more reliable sustainability reporting and
policy enforcement.
2. Conventions and Definitions
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
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3. Sustainability holistic API for Path Energy Evaluation (SHAPE)
This document describes an API to query a network about several
sustainability-related metrics for a given path. SHAPE extends PETRA
as defined in "draft-petra-path-energy-api-02" (IETF GREEN WG) with
additional sustainability metrics. It takes as input the source and
destination of a path along with the traffic throughput between and
returns energy information related to the traffic on the path. This
is energy computed by the infrastructure that is dynamically part of
the traffic path. The API is agnostic to the actual hops and
underlying infrastructure that enables a path, which might change
transparently to the API. This document only describes the API; the
computation of the energy information to return is out of the scope
of this document.
The API can return a variety of energy-related parameters to provide
a complete view of path sustainability. These include base
efficiency and footprint indicators (e.g., watts per gigabit and
carbon intensity), energy mix and renewable energy contributions, and
overhead and operational characteristics (e.g., transmission losses,
idle energy draw, cooling overheads, and the availability of low-
power states such as sleep modes).
In addition to point-in-time values, the API can expose temporal and
assurance-oriented information, such as the variability of carbon
intensity over a defined observation window, stability indices for
sustainability behavior (e.g., Sustainability Stability Index),
statistical measures of energy variability, anomaly signals, and
indicators of confidence in the underlying data sources. Such
metrics can help consumers distinguish persistent characteristics
from transient fluctuations.
Furthermore, the SHAPE's energy parameters complement ongoing work on
green service intents [I-D.irtf-nmrg-ibn-usecases], enabling
customers to express sustainability objectives such as energy
consumption thresholds, renewable energy usage, and carbon intensity
limits. SHAPE provides the underlying energy measurement interface
necessary for providers to fulfill, assure, and report on these green
intents. Moreover, by exposing detailed energy and carbon-related
parameters, SHAPE can allow intent translation components to map
green service objectives into network resource allocation and path
selection decisions.
3.1. Energy Information
This API allows to return a number of energy attributes associated
with the path and the traffic. Currently the parameters that could
be returned as energy information as part of the query are:
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* *Watts per Gigabit:* (Inherited from PETRA) How many Watts are
consumed per Gigabit of traffic traversing the path.
* *Carbon Intensity:* (Inherited from PETRA) How much carbon
emissions are generated as a consequence of the energy consumed.
* *Energy Mix (%):* Percentage of energy used in the path that comes
from different energy sources (e.g., solar, wind, biomass,
nuclear, fossil fuel).
* *Greenness Degree (%):* The aggregated percentage of energy
consumed on the path that comes from renewable sources. Useful to
rank and select paths based on renewable energy usage.
* *Sustainability Score (0–1):* Composite metric combining greenness
degree and energy efficiency (Watts per Gigabit), calculated as
(Greenness/100) × 1/(1 + Watts per Gigabit). Higher values
indicate more sustainable, efficient paths.
* *Power Usage Effectiveness (PUE):* The ratio of total facility
power consumption to the power consumption of networking/IT
equipment.
* *Transmission Loss (%):* The percentage of energy lost along the
path due to transmission inefficiencies.
* *Idle Energy Draw (Watts):* The amount of energy consumed by the
path infrastructure when idle or under negligible load.
* *Temporal Carbon Variability (TCV) (gCO2/kWh over period):*
Quantifies how much the carbon intensity of the electricity
powering the network path fluctuates over a defined time window
(e.g., 15 minutes, 1 hour, 24 hours). It reflects the stability
or volatility of the renewable/fossil mix affecting the path
during that period. A low TCV indicates predictable carbon
characteristics; a high TCV suggests inconsistent or rapidly
changing energy sources.
* *Sleep-mode Availability (%):* Measures the percentage of time
during which network devices or segments along a path support and
can enter low-power or idle energy-saving modes. It can also
reflect real usage of these modes depending on the operator’s
instrumentation (when supported or/and instrumented).
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* *Sustainability Stability Index (SSI) (0–1):* Quantifies the
stability over time of a sustainability metric (i.e., carbon
intensity or greenness degree), it is particularly relevant for
gSLAs, where predictable sustainability performance matters as
much as absolute values. Values close to 1 indicate highly stable
behavior.
* *Trustworthiness Score of Data Sources (TDS) (0–1):* characterizes
how reliable the API’s sustainability-related data is, based on
provenance, measurement quality, freshness, and cross-source
consistency. Higher values indicate stronger confidence in the
reported data.
* *Variance of Energy Consumption (VEC) (W^2):* VEC measures how
much the energy use of the path fluctuates during an observation
window. It helps detect energy instability, noisy equipment, or
poorly tuned power-management algorithms. High VEC indicates
unstable or erratic energy usage; low VEC indicates consistent
energy behavior.
* *Anomaly Factor (AF) (z-factor):* Identifies whether the energy
usage of a path at a given moment deviates significantly from its
historical baseline or expected statistical behavior, normalized
by standard deviation. AF < 1 indicates normal behavior, AF
around 2 indicates elevated deviation, and AF > 3 indicates an
anomaly (classic 3-sigma rule).
* *Cooling Energy Ratio (CER) (%):* Quantifies the share of total
energy consumed by a path or segment that is attributable to
cooling rather than networking/IT workload. It parallels PUE but
is per-path or per-segment, not facility-wide. Higher values
indicate higher cooling overhead relative to useful forwarding
energy.
These metrics are OPTIONAL, and an implementation MAY support a
subset depending on available measurement capabilities.
3.2. Recursive Usage
The API is envisioned in such a way that could be used recursively.
That means, subpaths could report their energy consumption using
SHAPE and such energy consumption could be aggregated and reported
for the overall path also using SHAPE.
Similarly, this API could be (recursively) used to provide energy
information according to the definition of Service Models in an SDN
context as described in [RFC8309]. In that case, using Figure 3 in
[RFC8309] as reference, SHAPE could be used between the Controller(s)
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and the Network Orchestrator(s), between the Network Orchestrator(s)
and the Service Orchestrator, and between the Service Orchestrator
and the Customer(s).
While considering recursive usage, the aspect of double-counting
shall also be taken into consideration. Double counting refers to
the fact of counting more than once the same energy consumed.
Organizations using SHAPE in a recursive manner need to take
appropriate measures to ensure no double-counting occurs across
recursive calls to the API.
Customer
------------------ Service ----------
| | Model | |
SHAPE as | Service |<-------->| Customer |
Customer Service | Orchestrator | (a) | |
related API | | ----------
------------------
. .
########################## . . (b) -----------
. (b) . ......|Application|
. . : | BSS/OSS |
SHAPE as . . : -----------
Service related API . Service Delivery . :
. Model . :
------------------ ------------------
| | | |
############# | Network | | Network |
| Orchestrator | | Orchestrator |
| | | |
.------------------ ------------------.
SHAPE as . : : .
Network API . : Network Configuration : .
. : Model : .
------------ ------------ ------------ ------------
| | | | | | | |
### | Controller | | Controller | | Controller | | Controller |
| | | | | | | |
------------ ------------ ------------ ------------
: . . : :
: . . Device : :
: . . Configuration : :
: . . Model : :
--------- --------- --------- --------- ---------
| Network | | Network | | Network | | Network | | Network |
| Element | | Element | | Element | | Element | | Element |
--------- --------- --------- --------- ---------
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4. YANG Module
SHAPE is specified as an augmentation to the PETRA YANG module
defined in [I-D.petra-green-api]. This section provides an example
YANG module, as per the YANG specification [RFC7950], that imports
PETRA and augments it with additional inputs and metrics.
4.1. Module Structure
module: irtf-shape
+--imports ietf-petra
augment /petra:energy/petra:query/petra:input:
+---w measurement-interval? uint32
+---w recursive? boolean
augment /petra:energy/petra:query/petra:output/petra:result/petra:success:
+--ro shape-metrics
+--ro energy-mix* -> list of sources and percentages
+--ro greenness-degree? decimal64
+--ro sustainability-score? decimal64
+--ro pue? decimal64
+--ro transmission-loss? decimal64
+--ro idle-watts? decimal64
+--ro temporal-carbon-variability? decimal64
+--ro sleep-mode-availability? decimal64
+--ro sustainability-stability-index? decimal64
+--ro trustworthiness-score? decimal64
+--ro variance-energy-consumption? decimal64
+--ro anomaly-factor? decimal64
+--ro cooling-energy-ratio? decimal64
4.2. Module Definition
module irtf-shape {
yang-version 1.1;
namespace "urn:ietf:params:xml:ns:yang:irtf-shape";
prefix shape;
import ietf-petra {
prefix petra;
}
organization
"IRTF SUSTAIN Research Group";
contact
"RG Web:
RG List: ";
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description
"Initial YANG module for SHAPE API, v1.0.0
SHAPE extends the PETRA YANG module ('draft-petra-path-energy-api')
with additional optional sustainability-related metrics and, where
needed, additional input parameters to qualify observation windows.
Copyright (c) 2026 IETF Trust and the persons identified as
authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject to
the license terms contained in, the Revised BSD License set
forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(https://trustee.ietf.org/license-info).
This version of this YANG module is part of RFC XXXX
(https://www.rfc-editor.org/info/rfcXXXX); see the RFC itself
for full legal notices.
The key words 'MUST', 'MUST NOT', 'REQUIRED', 'SHALL',
'SHALL NOT', 'SHOULD', 'SHOULD NOT', 'RECOMMENDED',
'NOT RECOMMENDED', 'MAY', and 'OPTIONAL' in this document
are to be interpreted as described in BCP 14 (RFC 2119)
(RFC 8174) when, and only when, they appear in all
capitals, as shown here.
";
/*
If you have an implementation of this YANG module, you could
access it like something this over RESTCONF:
$ curl --location --request POST \
'https://localhost:8008/restconf/operations/petra:energy/query' \
--header 'Content-Type: application/yang-data+json' \
--user 'admin:admin' \
--data-raw '{
"input" : {
"src-ip": "10.10.10.10",
"dst-ip": "10.20.20.20",
"throughput": 40,
"measurement-interval": 900,
"recursive": false
}
}'
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And if all goes well, you might receive (besides all the
HTTP headers) a reply body with something like this:
{
"output": {
"success": {
"watts-per-gigabit": 191.855,
"carbon-intensity": 108,
"shape-metrics": {
"energy-mix": [
{ "source": "solar", "percentage": 35.00 },
{ "source": "wind", "percentage": 25.00 },
{ "source": "gas", "percentage": 40.00 }
],
"greenness-degree": 60.00,
"sustainability-score": 0.312,
"pue": 1.20,
"transmission-loss": 3.50,
"idle-watts": 12.500,
"temporal-carbon-variability": 14.250,
"sleep-mode-availability": 20.00,
"sustainability-stability-index": 0.880,
"trustworthiness-score": 0.950,
"variance-energy-consumption": 1.750,
"anomaly-factor": 0.420,
"cooling-energy-ratio": 15.00
}
}
}
}
*/
revision 2026-02-26 {
description
"Initial SHAPE augmentation of PETRA, adding additional
sustainability metrics (including temporal/stability and
trustworthiness indicators).";
reference
"RFC XXXX: ...";
}
// ===== Groupings =====
grouping shape-metrics-g {
description
"Additional sustainability metrics defined by SHAPE that extend
the base PETRA query output.";
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list energy-mix {
key "source";
description
"Percentage contribution of each energy source to the total energy used on the path.";
leaf source {
type enumeration {
enum solar;
enum wind;
enum hydro;
enum nuclear;
enum coal;
enum gas;
enum biomass;
enum other;
}
description
"Type of energy source.";
}
leaf percentage {
type decimal64 {
fraction-digits 2;
range "0..100";
}
units "%";
description
"Percentage of path energy from this source.";
}
}
leaf greenness-degree {
type decimal64 {
fraction-digits 2;
range "0..100";
}
units "%";
description
"Aggregated percentage of energy from renewable sources.";
}
leaf sustainability-score {
type decimal64 {
fraction-digits 3;
range "0..1";
}
description
"Composite metric combining greenness degree and efficiency.
Suggested formula: (Greenness/100) × 1/(1 + Watts per Gigabit).";
}
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leaf pue {
type decimal64 {
fraction-digits 2;
range "1..max";
}
description
"Power Usage Effectiveness: ratio of total facility energy to IT/networking energy.";
}
leaf transmission-loss {
type decimal64 {
fraction-digits 2;
range "0..100";
}
units "%";
description
"Energy lost in transmission as percentage of total energy input.";
}
leaf idle-watts {
type decimal64 {
fraction-digits 3;
range "0..max";
}
units "W";
description
"Energy consumed by the path infrastructure when idle.";
}
leaf temporal-carbon-variability {
type decimal64 {
fraction-digits 3;
range "0..max";
}
units "gCO2e/kWh";
description
"Quantifies how much the carbon intensity powering the path fluctuates over
an observation window (e.g., 15 minutes, 1 hour, 24 hours).";
}
leaf sleep-mode-availability {
type decimal64 {
fraction-digits 2;
range "0..100";
}
units "%";
description
"Percentage of time during which devices or segments on the path can enter
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low-power or idle energy-saving modes (when supported and instrumented).";
}
leaf sustainability-stability-index {
type decimal64 {
fraction-digits 3;
range "0..1";
}
description
"Index (0..1) capturing the stability over time of a sustainability metric
(e.g., carbon intensity or greenness degree).";
}
leaf trustworthiness-score {
type decimal64 {
fraction-digits 3;
range "0..1";
}
description
"Composite score (0..1) reflecting reliability of reported sustainability data,
e.g., based on provenance, quality, freshness, and cross-source consistency.";
}
leaf variance-energy-consumption {
type decimal64 {
fraction-digits 3;
range "0..max";
}
units "W^2";
description
"Variance of energy consumption over an observation window.";
}
leaf anomaly-factor {
type decimal64 { fraction-digits 3; }
units "z-score";
description
"Deviation of current energy consumption from a historical mean, normalized
by standard deviation (z-factor).";
}
leaf cooling-energy-ratio {
type decimal64 {
fraction-digits 2;
range "0..100";
}
units "%";
description
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"Ratio between cooling energy and IT/network energy for a path or segment.";
}
}
// ===== Augmentations =====
augment "/petra:energy/petra:query/petra:input" {
description
"Additional optional input parameters for SHAPE that qualify the
observation window and, when supported, recursive collection.";
leaf measurement-interval {
type uint32 {
range "1..max";
}
units "seconds";
description
"Observation window used to compute time-dependent metrics (e.g., variability,
stability, variance, and anomaly indicators).";
}
leaf recursive {
type boolean;
default "false";
description
"Whether the query should be expanded recursively across multiple administrative
domains (if supported).";
}
}
augment "/petra:energy/petra:query/petra:output/petra:result" {
description
"Additional status/error cases for PETRA query output to support
scenarios where energy data is unavailable or only partially
available along the resolved path.";
case energy-unavailable {
container energy-unavailable {
description
"The path was resolved but energy data is not available
for one or more segments. No watts-per-gigabit can be
returned. Corresponds to accuracy-unavailable in the
GREEN data-source-accuracy hierarchy.";
}
}
case partial-result {
container partial-result {
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description
"Energy data is available for part of the path only.
The watts-per-gigabit returned covers the measurable
segments. The data-source-accuracy leaf SHOULD be set
to reflect the least accurate contributing measurement.";
uses energy-metrics-g;
}
}
}
augment "/petra:energy/petra:query/petra:output/petra:result/petra:success" {
description
"Add SHAPE sustainability metrics to the successful PETRA query result.";
container shape-metrics {
description
"Collection of additional sustainability metrics defined by SHAPE.";
uses shape-metrics-g;
}
}
}
5. Security Considerations
SHAPE queries and responses can reveal operational and business-
sensitive information (e.g., energy efficiency, carbon footprint,
facility overheads, and potentially location- or time-correlated
behavior). SHAPE API MAY be exposed via management protocols such as
NETCONF [RFC6241] and RESTCONF [RFC8040] and, therefore, it inherits
their security properties and deployment practices. Implementations
MUST consider the following aspects:
* *Secure transport:* Implementations MUST ensure confidentiality
and integrity protection for SHAPE exchanges (i.e., by using
secure transports mandated by the underlying management protocol).
Where RESTCONF is used, HTTPS is REQUIRED by [RFC8040].
* *Authentication and authorization:* SHAPE servers MUST
authenticate clients and MUST enforce authorization on a per-
request basis. Authorization SHOULD be granular (e.g., via
access-control mechanisms such as NACM [RFC8341]) and cover: (i)
which path endpoints can be queried, (ii) which metrics can be
returned (including SHAPE augmentations), and (iii) which
precision/granularity is permitted.
* *Information disclosure controls:* Returned sustainability data
(i.e., energy mix, PUE, cooling-energy ratio, or temporal
variability) can be used to infer facility characteristics,
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topology, utilization patterns, or operational policies. Servers
SHOULD support policy controls that reduce disclosure risk (e.g.,
aggregation, reduced precision, or suppressing specific metrics)
for less-privileged clients.
* *Input validation and bounds:* Servers MUST validate all inputs
(i.e., including path identifiers, throughput, measurement-
interval, and the recursive flag) and enforce reasonable bounds to
prevent expensive computations and state growth. In particular,
servers SHOULD enforce upper limits on observation-window
durations, recursion depth/scope, and the amount of per-request
data returned.
* *Denial-of-service resilience:* SHAPE computations may involve
multi-device sampling, aggregation, and historical lookups.
Servers SHOULD implement DoS mitigations such as rate limiting,
per-client quotas, request prioritization, and caching of commonly
requested results. If requests are rejected due to overload or
policy, servers SHOULD return explicit errors rather than silently
ignoring requests.
* *Multi-domain and recursive operation:* When the query is expanded
recursively across administrative domains, each domain MUST
enforce its own local policy and MUST NOT assume that ustream
requests are safe. Implementations SHOULD ensure that recursive
expansion does not leak credentials, does not bypass local
authorization, and does not create amplification (e.g., fan-out
storms). Responses obtained from external domains SHOULD be
treated as untrusted inputs.
* *Integrity of measurement chain:* SHAPE metrics can be used for
automated decisions (e.g., policy enforcement or gSLAs).
Implementations SHOULD protect the integrity of the measurement
pipeline (collection, aggregation, and publication) and SHOULD
provide operational mechanisms such as audit logs and provenance
tracking to help detect tampering or misconfiguration.
* *Privacy:* Sustainability metrics may correlate with customer
traffic patterns or reveal information about customer locations
and activity. Implementations SHOULD minimize retention of per-
customer/per-flow data and SHOULD protect logs and telemetry
derived from SHAPE requests.
6. IANA Considerations
This document has no IANA actions.
7. References
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7.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
.
[RFC3688] Mealling, M., "The IETF XML Registry", BCP 81, RFC 3688,
DOI 10.17487/RFC3688, January 2004,
.
[RFC6020] Bjorklund, M., Ed., "YANG - A Data Modeling Language for
the Network Configuration Protocol (NETCONF)", RFC 6020,
DOI 10.17487/RFC6020, October 2010,
.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
.
[RFC6242] Wasserman, M., "Using the NETCONF Protocol over Secure
Shell (SSH)", RFC 6242, DOI 10.17487/RFC6242, June 2011,
.
[RFC6991] Schoenwaelder, J., Ed., "Common YANG Data Types",
RFC 6991, DOI 10.17487/RFC6991, July 2013,
.
[RFC7950] Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
RFC 7950, DOI 10.17487/RFC7950, August 2016,
.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, .
[RFC8309] Wu, Q., Liu, W., and A. Farrel, "Service Models
Explained", RFC 8309, DOI 10.17487/RFC8309, January 2018,
.
[RFC8340] Bjorklund, M. and L. Berger, Ed., "YANG Tree Diagrams",
BCP 215, RFC 8340, DOI 10.17487/RFC8340, March 2018,
.
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[RFC8341] Bierman, A. and M. Bjorklund, "Network Configuration
Access Control Model", STD 91, RFC 8341,
DOI 10.17487/RFC8341, March 2018,
.
[RFC9315] Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", RFC 9315, DOI 10.17487/RFC9315, October
2022, .
7.2. Informative References
[I-D.bcmj-green-power-and-energy-yang]
Claise, B., Chen, G., Palmero, M. P., and J. Lindblad,
"Power and Energy YANG Module", Work in Progress,
Internet-Draft, draft-bcmj-green-power-and-energy-yang-02,
9 February 2026, .
[I-D.belmq-green-framework]
Claise, B., Contreras, L. M., Lindblad, J., Palmero, M.
P., Stephan, E., and Q. Wu, "Framework for Energy
Efficiency Management", Work in Progress, Internet-Draft,
draft-belmq-green-framework-10, 8 February 2026,
.
[I-D.irtf-nmrg-ibn-usecases]
Yao, K., Chen, D., Jeong, J. P., Wu, Q., Yang, C.,
Contreras, L. M., and G. Fioccola, "Use Cases and
Practices for Intent-Based Networking", Work in Progress,
Internet-Draft, draft-irtf-nmrg-ibn-usecases-02, 3
November 2025, .
[I-D.petra-green-api]
Rodriguez-Natal, A., Contreras, L. M., Palmero, M. P.,
Lindblad, J., and A. G. Sánchez, "Path Energy Traffic
Ratio API (PETRA)", Work in Progress, Internet-Draft,
draft-petra-green-api-02, 20 October 2025,
.
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Acknowledgments
The contribution of A. Gallego Sánchez to this document has been
partially supported by the Smart Networks and Services Joint
Undertaking (SNS JU) under the European Union's Horizon Europe
research and innovation project Sustain6G (Grant Agreement no.
101191936).
The contribution of L.M. Contreras to this document has been
partially 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).
Appendix A. Use Cases
This section describes some use-cases where this specification might
be useful.
A.1. SD-WAN
Software-Defined Wide-Area Networks (SD-WAN) have become a common way
for enterprises to provide cost-effective connectivity across their
different geographically distributed sites. Typically, SD-WAN
deployments operate as an overlay network that is established on top
of an existing underlay connectivity network. One aspect to consider
is that in many SD-WAN production deployments the operator of the
overlay network and the operator of the underlay network are
different organizations.
This poses an additional challenge when trying to derive
sustainability metrics. Even if the underlay network is instrumented
to collect energy data, this data is opaque to the operator of the
overlay network which has no access to underlay information. While
operators of underlay networks offer certain general network metrics
to overlay operators, no interface has been defined to allow the
overlay operator to query the underlay network for energy
information.
In this context, the SHAPE specification presented in this document
enables the operator of the SD-WAN network to coordinate with the
underlay operator to capture sustainability data. This in turns
opens further use-cases, from observability and reporting to
potentially overlay policies based on underlay energy data, further
enabling an overall more sustainable operation of the network.
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In addition to energy considerations in SD-WAN deployments, SHAPE can
also be leveraged for broader energy-aware service routing. In this
context, network controllers and service orchestrators—such as SD-WAN
controllers, transport SDN controllers, 5G slice orchestrators, or
multi-domain service orchestrators—can use SHAPE metrics not only to
balance latency, throughput, or load, but also to optimize path
selection according to sustainability objectives. For example, paths
with the lowest carbon intensity or the highest share of renewable
energy in their energy mix could be preferred, enabling service
differentiation where “green paths” are explicitly prioritized. This
brings a paradigm where routing decisions are jointly driven by
network performance and environmental impact.
A.2. Multilayer Energy Management
The concept of multilayer L3-L1 collection involves integrating data
from different network layers to provide a comprehensive view of
network operations. The use case of multilayer involves collecting
and correlating data from Layer 3 (network layer) down to Layer 1
(physical layer). This multilayer approach allows for better network
performance, optimization, and troubleshooting by providing end-to-
end visibility.
Leveraging SHAPE API for multilayer L3-L1 collection use case
enhances energy management by providing comprehensive visibility,
enabling optimization, and supporting proactive management. This
makes SHAPE a useful tool for more accurate, efficient and effective
energy management in modern networks.
A.3. SLA Negotiation for Green Services
Another use case for SHAPE could be the negotiation of green Service
Level Agreements (gSLAs) between operators and enterprise customers.
By exposing SHAPE-derived metrics such as renewable energy
percentage, carbon intensity, or sustainability scores, providers can
offer differentiated SLAs that explicitly include environmental
targets. This enables customers to select network services not only
based on performance guarantees, but also on their environmental
footprint, for example requesting that at least 60% of traffic be
carried over renewable-powered infrastructure. Such gSLAs empower
customers to align their digital services with corporate
sustainability goals and reporting requirements, while operators can
use SHAPE as the trusted source of verifiable energy data.
gSLAs can be negotiated using customer-expressed green intents that
specify objectives such as maximum energy consumption, minimum energy
efficiency, carbon emission limits, and renewable energy usage
[I-D.irtf-nmrg-ibn-usecases]. SHAPE's metrics, including watts per
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gigabit, carbon intensity, and energy mix, provide essential
measurements to translate these intents into network configurations
and to monitor compliance during service operation. The lifecycle of
green intents, encompassing fulfillment and assurance phases
[RFC9315], can be supported by SHAPE through its capability to
deliver real-time energy metrics for translation into network
policies and subsequent monitoring and validation.
Appendix B. Requirements for Energy Efficiency Management
The document Framework for Energy Efficiency Management
[I-D.belmq-green-framework] describes a framework that comprises a
controller element. In that document, the tasks of the controller
are defined as "collection, compute and aggregate". In the context
of that framework, the controller could also expose SHAPE to offer
path-related energy information. The figure below updates the one
present in [I-D.belmq-green-framework] to add an additional interface
(interface 'g') to the controller to represent the Path Traffic Ratio
API.
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+--------------------------------------------------------------------+
| |
| (3) Network Domain Level |
| |
+--------------------------------------------------------------------+
(a) (b) (c)
Inventory Monitor +- DataSheets/DataBase
Of identity Energy | and/or via API
and Capability Efficiency | Metadata and other
^ ^ | device/component/network
| | | related information: (g)
| | | SHAPE
| | | .Power/Energy related metrics API
| | | .information ^
| | | .origin of Energy Mix |
| | | .carbon aware based on location |
| | | |
| | v |
+--------------------------------------------------------------------+ |
| | |
| (2) controller (collection, compute and aggregate?) +-+
| |
+--------------------------------------------------------------------+
^ ^ ^ |
(d) | (e) | (f) | |
Inventory | Monitor power | Control | |
Capability | Proportion | (Energy saving | |
| Energy efficiency| Functionality | |
| ratio, power | Localized mgmt/ | |
| consumption, | network wide mgmt) | |
| etc) | | |
| | | v
+--------------------------------------------------------------------+
| |
| (1) Device/Component |
| |
| +---------+ +-----------+ +----------------+ +----------------+ |
| | (I) | | (II) | | (III) | | (IV) | |
| | | | | | Legacy | | 'Attached'(PoE | |
| | Device | | Component | | Device | | end Point) | |
| | | | | | | | | |
| +---------+ +-----------+ +----------------+ +----------------+ |
+--------------------------------------------------------------------+
Figure 1: SHAPE Integration in Energy Management Framework
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Authors' Addresses
Adrian Gallego Sanchez
Deutsche Telekom
Guadalajara
Spain
Email: ADRIAN.GALLEGO-SANCHEZ@t-systems.com
Alberto Rodriguez-Natal
Cisco
Madrid
Spain
Email: natal@cisco.com
Luis M. Contreras
Telefonica
Madrid
Spain
Email: luismiguel.contrerasmurillo@telefonica.com
Marisol Palmero
Toledo
Spain
Email: marisol.ietf@gmail.com
Jan Lindblad
All For Eco
Email: jan.lindblad+ietf@for.eco
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