Internet DRAFT - draft-cparsk-eimpact-sustainability-considerations
draft-cparsk-eimpact-sustainability-considerations
Network Working Group C. Pignataro, Ed.
Internet-Draft NC State University
Intended status: Informational A. Rezaki
Expires: 27 July 2024 Nokia
S. Krishnan
Cisco
H. ElBakoury
Independent Consultant
A. Clemm
Futurewei
24 January 2024
Sustainability Considerations for Internetworking
draft-cparsk-eimpact-sustainability-considerations-07
Abstract
This document defines a set of sustainability-related terms to be
used while describing and evaluating environmental impacts of
Internet technologies. It also describes several of the design
tradeoffs for trying to optimize for sustainability along with the
other common networking metrics such as performance and availability.
Embedding sustainability considerations at the design of new
protocols and extensions is more effective than attempting to do so
after-the-fact. Consequently, this document also gives network,
protocol, and application designers and implementors sustainability-
related advice and guideance. This document recommends to authors
and reviewers the inclusion of a Sustainability Considerations
section in IETF Internet-Drafts and RFCs.
Status of This Memo
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provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on 27 July 2024.
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Copyright Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Definition of Terms . . . . . . . . . . . . . . . . . . . . . 3
3. 'Sustainable X' versus 'X for Sustainability' . . . . . . . . 12
3.1. Sustainable Internetworking . . . . . . . . . . . . . . . 13
3.2. Internetworking for Sustainability . . . . . . . . . . . 15
4. Key Values and Key Value Indicators . . . . . . . . . . . . . 16
4.1. Key Value Enablers . . . . . . . . . . . . . . . . . . . 17
5. Implications to the IETF . . . . . . . . . . . . . . . . . . 18
6. Sustainability Considerations - How Will the Natural
Environment be Impacted? . . . . . . . . . . . . . . . . 18
6.1. Design Tradeoffs . . . . . . . . . . . . . . . . . . . . 18
6.2. Multi-Objective Optimization . . . . . . . . . . . . . . 19
6.3. How Much Resiliency is Really Needed? . . . . . . . . . . 20
6.3.1. Redundancy and Sustainability . . . . . . . . . . . . 20
6.4. How Much are Performance and Quality of Experience
Compromised? . . . . . . . . . . . . . . . . . . . . . . 21
6.5. End-to-End Sustainability . . . . . . . . . . . . . . . . 21
6.6. Attributional and Consequential Models . . . . . . . . . 22
6.7. The Role of Network Management and Orchestration . . . . 23
6.7.1. Metrics for Sustainability . . . . . . . . . . . . . 24
7. Sustainability Requirements and Phases . . . . . . . . . . . 24
7.1. Phase 1: Visibility . . . . . . . . . . . . . . . . . . . 24
7.2. Phase 2: Insights and Recommendations . . . . . . . . . . 25
7.3. Phase 3: Self-optimization and Automation . . . . . . . . 25
7.3.1. Cycle of Phases . . . . . . . . . . . . . . . . . . . 26
8. Sustainability Guidelines for Protocol and Network Designers
and Implementers . . . . . . . . . . . . . . . . . . . . 26
9. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 29
9.1. Call to Action . . . . . . . . . . . . . . . . . . . . . 29
10. Security Considerations . . . . . . . . . . . . . . . . . . . 29
11. Acknowledgements and Contributions . . . . . . . . . . . . . 30
12. Informative References . . . . . . . . . . . . . . . . . . . 30
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Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 33
1. Introduction
Over the past decade, there has been increased awareness of the
environmental impact produced by the widespread adoption of the
Internet and internetworking technologies. The impact of Internet
technologies has been overwhelmingly positive over the past years
(e.g., providing alternatives to travel, enabling remote and hybrid
work, enabling technology-based endangered species conservation,
etc.), and there is still room for improvement.
This document describes some of the tradeoffs that could be involved
while optimizing for sustainability in addition to or in lieu of
traditional metrics such as performance or availability. It also
proposes some common terminology for discussing environmental impacts
of Internet technologies, and gives network and protocol designers
and implementors sustainability-related advice and guideance.
Further, it discusses how Internet technologies can be used to help
other fields become more sustainable.
Specifically, this document is organized with the following outline:
* Section 2 includes a "Definition of Terms"
* Sections 3 through 7 detail sustainability and environmental
impact considerations, and their implications to Internet
protocols, architectures, and technologies.
* Section 8 lists "Sustainability Guidelines for Protocol and
Network Designers and Implementers"
The ultimate objective of this document is to detail guidance
regarding aspects of sustainability and environmental impact that
authors and reviewers of Internet protocol and architecture documents
should consider in a "Sustainability Considerations" section.
2. Definition of Terms
Given that the term 'considerations' is well known within the IETF
community, it is fair to start by defining 'sustainability'. The
1983 UN Commission on Environment and Development had important
influence on the current use of the term. The commission's 1987
report [UNGA42] defines it as development that "meets the needs of
the present without compromising the ability of future generations to
meet their own needs". This in turn involves balancing economic,
social, and environmental factors.
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This section defines sustainability-specific terms as they are used
in the document, and as they pertain to environmental impacts. The
goal is to provide a common sustainability considerations lexicon for
network equipment vendors, operators, designers, and architects.
Notwithstanding the most comprehensive set of definitions of relevant
terms readers can find at [IPCC], this section contributes the
application and exemplification of the terminology to the
internetworking domain and field. The terms are alphabetically
organized.
Appropriate technology:
formerly referred to as 'intermediate technology', it refers to
technology that is adapted to the local needs of its users, that
is affordable, sustainable, and usually small scale and
decentralized. Globally impactful technology is to be adaptable
to local contexts it is used in. Regarding internetworking, there
could be linkages to centralization / decentralization challenges,
as well as maintainability & deployability aspects. Considering
the diversity of local contexts, from developed countries with
remote/rural coverage/access issues, to developing countries with
unstable electricity grids as well as literacy and technology
usability/accessibility issues, internetworking technology needs
to be designed, developed and operated according to these local
requirements, also supporting small scale business models to make
impact.
Biodiversity loss:
Biological diversity is a measure of the abundance and variety of
life on earth. Biodiversity loss is the depletion of this
diversity due to human activity, notably through the destruction
of natural ecosystems and through the cascading effects of climate
change, materials extraction, waste disposal and pollution, among
other impacts, on the living world and species.
CO2e / CO2eq / CO2-eq:
Carbon dioxide equivalent, is the unit for measuring the climate
change impact of non-CO2 gases as compared to CO2, which is
selected as a benchmark.
Carbon awareness:
is being mindful of the carbon intensity of the electricity being
used and prioritizing the use of low carbon intensity electricity
in network set-up and operations. As carbon intensity is location
and time dependent, carbon awareness requires dynamic monitoring
and response, such as carbon aware routing and networking. This
is a form of "demand shaping" which aims to match the use of
energy with the supply of clean energy.
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Carbon intensity (CI):
also referred to as emission intensity and emission factor, is a
measure of the carbon-equivalent emission of consumed electricity,
i.e., grams of carbon-equivalent per kilowatt hour (gCO2e/KWh).
When the supplied energy mix is purely from renewable sources such
as sun and wind, carbon intensity is practically 0, when coal and
gas-powered electricity generation gets in the mix, carbon
intensity increases. Carbon intensity could change
instantaneously or predictably based on the time and location of
electricity use. Prioritizing electricity use when carbon
intensity is low is a target.
Carbon offset and credit:
is a reduction of GHGs from the atmosphere as compensation for
GHGs produced elsewhere and the credit generated and used
respectively. This reduction in GHG emissions can be an increase
in carbon storage through land restauration, or an actual removal
of GHG. For example, certified forestation projects that absorb
carbon dioxide produce carbon credits that an airline can use to
offset its GHG emissions by using (purchasing) these credits.
There are accredited carbon trading mechanisms to facilitate this
exchange. This is generally regarded as a non-scalable solution,
and activities such as the reduction of GHG emissions and the
shifting of electrical energy production to renewables are a
primary focus.
Circularity (circular economy):
is a model or system where material resources and products are
kept in use for as long as possible through long life cycles,
reuse, repair, refurbishing and recycling, thereby reducing
materials use, waste, and pollution as well as biodiversity and
geodiversity loss. Keeping internetworking equipment in longer
use through modularity, serviceability, upgradeability,
maintainability are strategies to improve circularity.
Climate change (climate emergency, global warming):
can be summarized as the increase in the global average
temperatures and its destructive impact on life on Earth. The
climate emergency refers to the ongoing and projected impacts of
rising global temperatures and the narrow time window we have to
limit temperature increases to a threshold determined by the Paris
Climate Agreement (2015) to avoid the permanent destabilization of
Earth life-support systems.
Climate change adaptation:
are the measures we can take to adjust ourselves to the already
happening and projected future adverse effects of climate change.
This notably includes raising the resilience of internetworking
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solutions to higher operating temperatures and other impacts of
climate change, as well as the use of internetworking technology
to increase the resilience of societies and nature itself.
Climate change mitigation:
encompasses all measures to reduce the impact of climate change.
More specifically, any measures that reduce the amount of GHGs in
the atmosphere can be considered as climate change mitigation
through reduced inflow of GHGs into the atmosphere (such as
burning of fossil fuels) or increasing the impact of carbon sinks
such as forests and oceans. Reducing the carbon footprint of
internetworking and increasing its carbon handprint by helping
other sectors to decarbonize are mitigation efforts.
CUE:
Carbon usage effectiveness [CUE] is a metric that helps determine
the amount of greenhouse gas (GHG) emissions produced per unit of
IT energy consumed within a data center. It provides an effective
way to measure operational carbon footprint and thus the
environmental impact of data center operations. The CUE is the
ratio of the total CO2 emissions caused by total data center
energy consumption, divided by the energy consumption of IT
equipment. To calculate CUE when using electricity from the grid,
carbon emissions can be based on published data. See also "PUE".
Doughnut economics:
is a visual framework for sustainable development. It attempts to
find a safe operational space within planetary boundaries and
complementary (yet seemingly opposing) social boundaries, thereby
meeting the needs of human societies without pushing earth
environmental boundaries to their tipping points [Doughnut]. The
significance of this model for interworking is that it
demonstrates how to conceptualize and position boundaries in our
designs that are seemingly opposing, to create a balanced
approach, for example between energy efficiency and performance or
resiliency and materials efficiency. It is not one or the other,
but to find a space where both can be achieved without crossing
boundaries in respective domains.
Embodied emissions:
also referred to as embodied carbon and embedded carbon, refers to
the amount of GHG emissions associated with upstream phases - raw
material extraction, production, transportation (of materials and
of product), and manufacturing-stages of a product's lifecycle.
Some initiatives also consider disposal.
Energy, power, and their measurement:
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In physics, energy is defined as the capacity or ability to do
work. For a system to provide an output, the quantitative
property of energy is transferred to it. The energy measurement
unit in the International System of Units (SI) is the joule (J).
Power is energy used per second, measured in the International
System of Units in watts (W), equivalent to the rate of one joule
per second (J/s). In other words, energy is the integration of
power over time. As such, Kilowatt-hour (kWh) is also a measure
of energy, equivalent to 1 kW of power maintained for 1 hour,
which is equal to 3.6 MJ (million joules).
Energy efficiency (EE):
increased energy efficiency can be summarized as doing the same
task with less energy use, that is, providing a useful output/
impact with as little energy as possible, eliminating energy
waste. Switching to more efficient power supplies and silicon or
developing more efficient transmission or signal processing
algorithms improves EE. Developing energy efficiency metrics for
internetworking and associated measurement methodologies and
conditions as well as consistently collecting this data over time
are essential to demonstrating EE improvements. An example of a
common outcome-oriented metric is energy consumption per data
volume or traffic unit, in Wh/B [Telefonica]; this particular
metric has however also been criticized for being easy to
misinterpret, falsely indicating that systems are energy
proportional even when they are not (see "Energy
proportionality".)
Energy equity:
Energy equity aims to minimize the negative impacts of energy
systems and maximize the benefits for all energy users.
Historically, these impacts and benefits haven't been equitably
distributed. Energy equity recognizes that disadvantaged
communities have been historically marginalized and overburdened
by pollution, underinvestment in clean energy infrastructure, and
lack of access to energy efficient housing and transportation.
Energy proportionality:
is the correlation between energy used and the associated useful
output. For internetworking this is generally interpreted as the
proportionality of traffic or traffic throughput and energy used.
This concept is broadly applicable to networking infrastructure,
data center, and other communication architectures. It is not a
given that there is a one-to-one correlation between traffic and
energy use, notably due to the materially significant idle power
use by devices, as well as the overall network capacity being
allocated to serve at times of highest traffic utilization.
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Energy savings / conservation (ES):
is the avoidance of energy use, by eliminating a task altogether,
when possible. Shutting down unused ports on a networking
equipment is energy savings/conservation.
Footprint (environmental/ecological):
in general terms is the impact we have on the planet. It can be
divided into subcategories as carbon footprint, water footprint,
land footprint, biodiversity footprint, etc. Related to the
climate emergency, we are mostly focused on our carbon footprint,
however, it has been shown that sub-categories of footprint are
not entirely independent of each other. For example, our carbon
footprint has a proven impact on the climate emergency through
rising global temperatures, cascading significant impact on forest
cover in warming areas since tree species adapted to certain
climates vanish, thereby reducing biodiversity in that region, in-
return impacting the carbon sink properties of the environment and
exacerbating climate change. A holistic approach to our
environmental footprint would therefore provide the best
opportunity to create impact.
GHGs:
Greenhouse gases are types of gases that trap heat from the sun in
earth's atmosphere, thereby increasing average global temperatures
and creating the climate emergency. Carbon dioxide (CO2) is one
of the most common (and referenced) greenhouse gases. There are
others such as methane (CH4 - a much more potent GHG than CO2) and
sulfur hexafluoride (SF6 - an artificial electrical insulator with
tens of thousands of times more warming effect than CO2).
GHG Emissions Scopes:
According to the Greenhouse Gas (GHG) Protocol [GHG-Proto],
Chapter 4, the emissions scopes are defined as below:
* Direct GHG emissions are emissions from sources that are owned
or controlled by the company.
* Indirect GHG emissions are emissions that are a consequence of
the activities of the company but occur at sources owned or
controlled by another company.
The GHG protocol [GHG-Proto], Chapter 4, also includes the
following descriptions of emissions scopes for accounting and
reporting purposes:
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* Scope 1 Emissions: Direct GHG emissions - Direct GHG emissions
occur from sources that are owned or controlled by the company,
for example, emissions from combustion in owned or controlled
boilers, furnaces, vehicles, etc.; emissions from chemical
production in owned or controlled process equipment.
* Scope 2 Emissions: Electricity indirect GHG emissions - Scope 2
accounts for GHG emissions from the generation of purchased
electricity consumed by the company. Purchased electricity is
defined as electricity that is purchased or otherwise brought
into the organizational boundary of the company. Scope 2
emissions physically occur at the facility where electricity is
generated.
* Companies shall separately account for and report on scopes 1
and 2 at a minimum.
* Scope 3 Emissions: Other indirect GHG emissions - Scope 3 is an
optional reporting category that allows for the treatment of
all other indirect emissions. Scope 3 emissions are a
consequence of the activities of the company, but occur from
sources not owned or controlled by the company. Some examples
of scope 3 activities are extraction and production of
purchased materials; transportation of purchased fuels; and use
of sold products and services.
In telecommunications networks, Scope 3 emissions include the use
phase of the sold products in operations, and is currently the
largest part by far, of the whole GHG emissions (Scopes 1, 2 and
3), depending on the carbon intensity of the energy supply in use.
GWP:
Global warming potential, is the potential impact of GHGs on
climate change, measured in CO2e.
Geodiversity:
is the variety of the nonliving parts of nature, that is, the
materials constituting Earth, including soils, water (rivers,
lakes, oceans), minerals, landforms and the associated processes
that form and change them. The materials used in the production
of internetworking equipment as well as their manufacturing and
operational processes themselves, have impact (footprint) on
geodiversity. Materials efficiency as well as circularity
improvements help mitigate this impact.
Handprint (environmental/ecological):
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is a concept developed in contrast to footprint, to quantify and
demonstrate the positive environmental/ecological impact of
technologies, products or organizations. Through a LCA (life
cycle assessment) approach, the use of a technology or the
products and services of an organization would have both a
footprint and handprint usually denoted by the terms "X for
sustainability" (handprint) and "Sustainable X" (footprint). What
is important is that handprint impact does not compensate for
footprint impact. They are to be calculated and reported
independently; footprint to be minimized as much as possible, and
handprint maximized as much as possible, which are by definition
different activities anyway. Otherwise, this might be construed
as "greenwashing". A popular seesaw figure in common
sustainability literature depicting handprint and footprint
sitting on opposite ends of a seesaw, one going up while the other
is going down is a misguided representation.
LCA (Life Cycle Assessment):
is a comprehensive methodology to measure the environmental impact
of a product, service, or process over its complete lifecycle,
from the extraction and procurement of materials, through design,
manufacturing, distribution, deployment, operations (use),
maintenance/repair, decommissioning, refurbishment/reuse,
recycling and disposal (waste), considering the full upstream and
downstream supply chains as well. It is an extremely complicated
process and there are multiple methods used worldwide, which might
not produce same/similar results. LCA covers full footprint
aspects, not only covering carbon, but also materials and
biodiversity. Please refer to Section 6.6 for additional details
on "Attributional and Consequential Models".
Materials efficiency and reuse:
is the concept of using less primary and (more) recycled materials
to provide the same output. A networking equipment that provides
the same function with less aluminium used is more materials
efficient. Reuse of materials in manufacturing, thereby reducing
primary materials extraction is a cornerstone of circularity,
reducing environmental footprint and promoting geodiversity.
Net-zero:
in general, is to bring down GHGs as close to zero as possible.
It is generally recognized that it may not be possible to get GHGs
to 0 in many contexts and the balance is said to be covered by
carbon offset. For example, many organizations and countries have
net-zero targets by certain dates and typically what they mean is
that they will reduce their GHGs by more than 90% and the
remaining up to 10% will be offset.
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PUE:
Power usage effectiveness, is a data centre energy efficiency
metric. The PUE is defined by dividing the total amount of power
entering a data center by the power used solely to run the IT
equipment within it. PUE is expressed as a ratio, with the
overall power usage effectiveneess improving as the quotient
decreases towards one. See also "CUE".
Planetary boundaries:
is a concept that defines 9 environmental boundaries that, if not
crossed, provides a safe space for humanity to live. This was
developed and tracked by the Stockholm Resilience Centre
[Planet-B]. Their latest report indicates that 6 out of the 9
boundaries have already been crossed. This translates to the
increased risk of irreversible environmental change, the so-called
tipping points. Climate change is one of these boundaries,
represented as carbon dioxide concentration in the atmosphere (ppm
by volume) and others are biodiversity loss, land use, fresh
water, ocean acidification, chemical pollution, ozone depletion
(one boundary that has been successfully mitigated), atmospheric
aerosols and biogeochemical (nitrogen in the atmosphere and
phosphorus in oceans).
Rebound effect:
is the reduction in the potential benefits of more efficient
technologies and solutions to reduce resource use, due to the
increased demand they might trigger as costs might decrease, in
return even increasing the overall resource use. This is known as
Jevons paradox: efficiency leading to increased demand. In
internetworking, this can manifest itself when more energy and
resource efficient systems reduce the cost for infrastructure
build and operations and when this is reflected to customers as
reduced cost, customers respond by increased use of
telecommunications services which pushes infrastructure build and
operations upwards, thereby negating the projected gains from
efficiency measures. Another descriptive source for this
phenomenon can be found at [Frontiers].
Tipping points:
are critical environmental thresholds, which when crossed likely
lead to irreversible state changes in climate systems that might
push the overall earth system out of its stable state that
supports life on Earth. For example, there are tipping points
defined for the Antarctic and Greenland ice sheets disappearing,
the Arctic sea-ice loss, Siberian permafrost loss or the dieback
of the Amazon and Boreal forests. As planetary boundaries are
crossed, the likelihood of the tipping points being reached also
increases. When the tipping points are hit, notably
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simultaneously, the overall impact to the global Earth system
might be catastrophic, as another stable state which no longer
supports life could be reached.
UN SDGs:
United Nations Sustainable Development Goals are 17 global
objectives that collectively define a framework for a sustainable
global system where people and the planet collectively thrive and
live in peace, prosperity and equity. They were adopted in 2015
and most of them have a target achievement date of 2030 [UN-SDG].
They are part of the so-called UN 2030 Agenda. The International
Telecommunications Union (ITU) has published on how our technology
could help meet the UN SDGs [ITU-ICT-SDG]. Notably, most UN SDGs
provide guidance for the handprint impact of internetworking
technologies, while some are also related to potential action for
footprint reduction. The 17 SDGs are:
Goal 1 No poverty
Goal 2 Zero hunger
Goal 3 Good health and well-being
Goal 4 Quality education
Goal 5 Gender equality
Goal 6 Clean water and sanitation
Goal 7 Affordable and clean energy
Goal 8 Decent work and economic growth
Goal 9 Industry, innovation and infrastructure
Goal 10 Reduced inequalities
Goal 11 Sustainable cities and communities
Goal 12 Responsible consumption and production
Goal 13 Climate action
Goal 14 Life below water
Goal 15 Life on land
Goal 16 Peace, justice and strong institutions
Goal 17 Partnerships for the Goals
The SDG Academy [SDG-Acad] also provides useful information on the
topic, as well as progress to date.
3. 'Sustainable X' versus 'X for Sustainability'
Every technology solution, system or process has sustainability
impacts, as it uses energy and resources and operates in a given
context to provide a [perceived] useful output. These impacts could
be both negative and positive w.r.t sustainability outcomes. With a
simplistic view, the negative impact is termed as footprint and the
positive impact is handprint, as defined in the "Definition of Terms"
section. Again, generally speaking, footprint considerations of a
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technology are grouped under "Sustainable X" and the handprint
considerations are covered under "X for Sustainability".
Additionally, when sustainability impacts are considered, not only
environmental but also societal and economic perspectives need to be
taken into account, both for footprint and handprint domains. A
systems perspective ensures that the interactions and feedback loops
are not forgotten among different sub-areas of sustainability.
Another fundamental sustainability impact assessment requirement is
to cover the complete impact of a product, service or process over
its full lifetime. Life Cycle Assessment (LCA) starts from the raw
materials extraction & acquisition phases, and continues with design,
manufacturing, distribution, deployment, use, maintenance,
decommissioning, refurbishment/reuse, and ends with end-of-life
treatment (recycling & waste). It is imperative that we consider not
only the design and build stages of our technologies but also its use
and end-of-life phases. An equally essential way of ensuring a
holistic perspective is the supply-chain dimension. When we consider
the footprint impact of a technology we are building, we need to
consider the full supply chain that the technology is part of, both
upstream, what it inherits from the material acquisition, components
and services used, to downstream for wherever the technology is used
and then decommissioned. Further, this includes transportation of
materials or products, and the carbon-friendliness of the means and
routes chosen. What this implies is that we are responsible for the
direct and indirect impacts of our activity, both on demand and
supply directions.
Below, we cover the "Sustainable Internetworking" and
"Internetworking for Sustainability" perspectives in more detail.
3.1. Sustainable Internetworking
Sustainable internetworking is about ensuring that the negative
impacts of internetworking are minimized as much as possible.
In the environmental / ecological sustainability domain, the sub-
areas to be considered are:
* Climate change,
* materials efficiency, circularity, preservation of geodiversity,
and
* biodiversity preservation.
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Climate change considerations in internetworking by and large
translate to energy sourcing, consumption, savings and efficiency as
this impacts the GHGs of the internetworking systems directly, when
mostly non-renewable energy sources are used for the operations of
the networks. When the carbon intensity of the energy supply used in
operations decreases (more renewable energy in the supply mix), then
the use phase GHGs also proportionally decrease. This might put the
GHG emissions of the manufacturing and materials extraction and
acquisition phases ahead of the use phase. These are called the
embodied emissions.
However, energy is not the only aspect to consider: materials
efficiency and circularity are key considerations to limit the
resource use of our technologies, thereby reducing the scarcity of
materials but also the destruction of many ecosystems during their
extraction and manufacturing, polluting water and land with waste,
which might also impact directly or indirectly the abundance and
health of the species on the planet, namely biodiversity. While it
is significantly more difficult to quantify and measure the impact of
our technologies in these domains, the planetary boundaries framework
provides helpful guidance.
For the societal and economic footprint of our technologies, we need
to be mindful about the potential negative effects of our
technologies w.r.t. the social boundaries, as depicted in the so-
called doughnut economics model, that includes education, health,
incomes, housing, gender equality, social equity, inclusiveness,
justice and more. What we need to realize is that our technology has
direct and indirect impacts in these aspects and the challenge is not
only to meet environmental sustainability targets but social and
economic ones as well. There are very practical considerations, for
example: are there partial or total barriers to accessing the
Internet or its services? what is the impact of biases in artificial
intelligence (AI), as it pertains gender biases, when those AI models
are used in job selection? More technology doesn't always mean
better outcomes for all and can we mitigate this impact? Admittedly,
a quantitative approach to the societal and economical aspects is
more challenging; thinking in terms of profit, people, and planet, as
well as the Key Values (KV) / Key Value Indicators (KVIs) approach
described in Section 4 bring some relief.
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3.2. Internetworking for Sustainability
When it comes to the positive impact of internetworking in tackling
the sustainability challenges faced, we are in the "internetworking
for sustainability" realm. This is a very diverse topic covering
innumerable industrial and societal verticals and use cases.
Essentially, we are asking how our technology can help other sectors
and users to decarbonize, and to reduce their own footprints and to
increase their handprints in environmental, societal and economic
dimensions. These are induced or enablement effects. Examples are
how internetworking is being used in smart energy grids or smart
cities, transport, health care, education, agriculture, manufacturing
and other verticals. While efficiency gains are usually a basis,
there are also other impacts through ubiquitous network coverage,
sensing, affordability, ease of maintenance and operation, equity in
access, to name a few.
Climate change mitigation and climate change adaptation, as defined
in the "Definition of Terms" section, are particular focus areas
where internetworking could help create more resilience in our
societies and economies along with sustainability.
Essentially, handprint considerations are asking us to think about
how our technology could be used to tackle sustainability challenges
at first, and second, to generate feedback on how to create enablers
and improvements in our technology for it to be more impactful. The
usual Key Performance Indicators (KPIs) related to technical system
parameters would be largely insufficient for this purpose.
Supporting this effort, the Key Values (KV) and Key Value Indicators
(KVIs) concepts have been developed, to be used in conjunction with
use cases to develop impactful solutions. KV and KVIs are the
subject of Section 4.
The following are some examples of internetworking for
sustainability. This is not a comprehensive list; many more such
examples can be found. Leveraging internetworking for sustainability
usually involves special requirements, which are listed along with
the examples.
Smart Grid:
The Smart Grid [RFC6272] generally refers to enhancements to
traditional electrical grids that offer additional features such
as two-way flows of electricity (e.g., accommodating solar panels,
electrical batteries) and granular control of the grid (e.g.,
allowing to selectively turn off certain consumers such as
Heating, Ventilation, and Air Conditioning (HVAC) units during
certain times.) The Smart Grid aims to improve sustainability by
facilitating concepts such as peak shaving (i.e., lowering peak
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usage to reduce the amount of excess generation of electricity
that is not needed during non-peak periods), and encouraging
residential homes and business to invest in renewable energy
sources such as solar, for example offering credit for feeding
surplus energy being generated back into the grid. For this to
work, the Smart Grid requires support by networking technology
that enables the required control loops as well as visibility into
grid telemetry. This, in turn, requires the support of new
requirements, including aspects of security (since a critical
infrastructure is at stake), adherence to high precision service
levels and ultra-low latency communication (e.g., to mitigate
sudden spikes in voltage), and special provisions to ensure data
privacy (given that data from private households, electrical
vehicles, and personal devices is involved.)
Smart Cities:
Many applications for smart cities involve optimizations to make
cities more sustainable. Examples include smart garbage disposals
that reduce the number of truck rolls (and associated emissions)
to collect garbage only when needed, and guidance systems for
smart parking that reduce the amount of vehicle traffic used to
find parking spots. These applications are enabled by networking.
Again, special requirements need to be supported for networks to
support those applications, such as the ability to deploy
equipment in harsh urban environments, or monitoring for
vandalism.
Smart Agriculture:
Smart agriculture involves minimizing usage of resources such as
fertilizer and water in the production of agricultural output.
This also helps minimize the area set aside for farming and
reclaim land for other purposes including biodiversity.
Similarly, networking is an enabler for environmental
sustainability. Special requirements for applications in this
space include aspects such as the ability to support networking
equipment without the need to run power lines (e.g., using battery
or solar), and support for intermittent communications.
4. Key Values and Key Value Indicators
In the context of sustainability, key values are what matters to
societies and to people when it comes to direct and indirect outcomes
of the use of our technology. While KPIs help us to build, monitor
and improve the design and implementation of our technologies, key
values and their qualitative and quantitative indicators tell us
about their usefulness and value to society and people. As we want
our technology to help tackle the grand challenges of our planet,
their likelihood of usefulness and impact is a paramount
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consideration. KVs and KVIs help set our bearings right and also
demonstrate the impact we could create. The main idea is shifting
from measuring performance to measuring value.
While key values could be universal, like for example the United
Nations Sustainable Development Goals (UN SDGs) [UN-SDG], how they
are measured, or perceived (KVIs) could be context dependent and use
case specific. To give a simplified example, UN SDG 3, "good health
and well-being" is a key value for any society and individual. Then,
when we consider the use case of providing health care and wellness
services in a remote, rural community which doesn't have any
hospitals or specialist doctors, a key value indicator could be how
fast a patient could access health care services without having to
travel out of town, or the successful medical interventions that
could be carried out remotely. Then the next step is to identify
which parts of our technology could help enable this and design our
technology to create impact for the KVs as per KVIs. In this case,
universal network coverage, capacity and features to integrate a
multitude of sensors, low-latency and jitter communication services
could all be enablers with their own design targets and KPIs defined.
Subsequently, we would track the KVIs and the KPIs together for
successful outcomes.
Admittedly, this might not be a straightforward task to carry out for
each protocol design. Yet, such analyses could be included in design
processes along with use case development, covering a group of
technology design activities (protocols) together. There are ongoing
efforts in mobile networking research to use KVs/KVIs efficiently
[M6G-SOCIETAL-KV-KVI] [M6G-VALUE-PERF] [Hexa-X_D1.2].
While we find ourselves trying to optimize seemingly contradicting
parameters or aspects such as reducing latency and jitter and
increasing bandwidth and reach targets with sustainability parameters
or aspects such as reduced energy consumption and increased energy
efficiency, key values and key value indicators would help keep our
eyes on the targets that matter for the end users and communities and
societies. Considerations for such potential design trade-offs,
which are at the heart of our engineering innovations, are the topic
of the next section.
4.1. Key Value Enablers
Between the design and creation of a technology, and realization of
the value generated by its deployment and use, there are a number of
enablers and blockers of its usage. We generally refer to them as KV
Enablers. These are the key factors that would scale and spread use
cases or block their deployment.
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Technical enablers are the features needed for the technical
capabilities and feasibility of the use cases, like the network
features being deployed to support the use case. Beyond the
technical aspects, there are also criteria at the system level which
determine the context in which the technology will be used as well as
the actions of the use case stakeholders. These might affect the
level of adaptation to a particular society or ecosystem, such as
cost of connectivity and Internet service access, availability of
services, security, and privacy. While technical enablers are in
more direct control of protocol and network designers, system-level
enablers might in second-order, indirect, or beyond control,
depending on the actions of other stakeholders and the existing
environment.
An important corollary is that KV enablers can be used to derive
technological requirements, KPIs and advancements to maximize key
value.
5. Implications to the IETF
This section describes the implications of sustainability to the
IETF. Specifically, the high-level relevant areas on which the IETF
can act upon, and a rough prioritization. These potentially include
use cases, protocols, metrics, etc.
A key area to understand the relevance and implication is regarding
IETF Protocols.
6. Sustainability Considerations - How Will the Natural Environment be
Impacted?
6.1. Design Tradeoffs
Traditionally, digital communication networks are optimized for a
specific set of criteria that proxies for business metrics. A
network operator providing services to their customers intends to
maximize profits, by increasing top-line revenue and decreasing
bottom-line associated costs. This directly translates to goals of
optimizing performance and availability, while reducing various
costs.
Most recently, various forces elevate the need for sustainability in
networking technologies and architectures, to quantify and minimize
negative environmental impact.
Optimizing only network availability (e.g., by having excess capacity
and backup paths) or optimizing only performance (e.g., by increasing
speeds selecting paths based on delays only) can seemengly be in
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opposition to optimizing sustainability objectives. For a given
application, use-case, or vertical realization of technology, a
Pareto-efficient choice can potentially improve sustainability
without sacrificing availability or performance beyond the
application tolerance. That is, a win-win.
Consequently, network architects and designers are presented with a
set of new design tradeoffs: a multi-objective optimization that
satisfies border requirements and global optima for availability,
performance, and sustainability simultaneously. This is not unlike
the doughnut economics model concept introduced in the "Definition of
Terms" section.
6.2. Multi-Objective Optimization
To understand this new model, we can analyze a simplified example.
Assume the following topology, passing traffic from A to B:
A
|
+----------+
| Router 1 |------------+
+----------+ |
| | | | | +----------+
| | | | | | Router 3 |
| | | | | +----------+
+----------+ |
| Router 2 |------------+
+----------+
|
B
Figure 1: Simplified Network for Multi-Objective Optimization
Router 1 is directly connected to Router 2 through five parallel
links, of 10 Gbps each. Router 1 can also reach Router 2 through
Router 3 with 40 Gbps links between Router 1 and Router 3, and
between Router 3 and Router 2. Let's assume that the capacity-
planned traffic between A and B equals 15 Gbps.
In this scenario, a topology optimized for performance and
availability/resiliency would have all links and routers on, and
would likely forward traffic using two of the parallel links.
Utilizing the path through Router 3 might lower performance, but it
serves as a backup path.
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On the other hand, when we add sustainability as a consideration,
different options are presented. One of them is to remove from the
topology Router 3 and associated links, and shutdown links and optics
in two or three of the parallel links. Another option is to
completely shutdown all the parallel links and route traffic through
Router 3 (i.e., not maximizing performance alone, but maximizing at
the time performance, availability and resiliency, and
sustainability.) The choice between these two options will depend on
the aggregate sustainability metrics of network elements in each of
the two topologies.
Another option is to use flexible Ethernet, where the five links
combined are aggregated into one active virtual link which has 15
Gbps, and another inactive link of 35 Gbps of capacity -- although a
physical link cannot be half-active and half-inactive as far as PHY
and optics are concerned.
6.3. How Much Resiliency is Really Needed?
When we add sustainability considerations, resiliency is not the
single objective to optimize.
There are many methods to improve network resiliency, including a
design eliminating single-points-of-failure, performing software
safe-release selections and upgrades, deploying network real-time
testing systems (including operations, administration, and
maintenance (OAM) tools, monitoring systems (e.g., [RFC8403]), chaos-
based testing, and site reliability engineering (SRE) principles),
and utilizing redundancy across network elements as well as across a
topology. Each one of these methods incurs also a sustainability
cost. Yet, the functions for resiliency improvement and
sustainability cost for each of these methods are not the same.
Considering sustainability means quantifying its impact in the
decision of how to improve resiliency, and how much is needed.
6.3.1. Redundancy and Sustainability
Let's first explore redundancy. For example, consider the ratio of
overall network capacity (in bandwidth, compute power, etc.) over the
used network capacity, and let's call it "Redundancy Index". If this
number is one, there's no redundancy; and as the ratio grows, so does
the potentially unused capacity that could be utilized in a failure
event. Similarly, consider the values of sustainability metrics for
when the Redundancy Index is one and for when it is two. These
border points might give an indication of the slope for each
objective function.
Adequate Redundancy:
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In order to determine how much redundancy needs to be built into
the overall network capacity, which can be referred to as
"adequate redundancy to avoid network outings", it will be
important to (1) measure the bandwidth of attacks against the
overall network capacity; and (2) understand how quickly "high
bandwidth" attacks can be detected and diverted. Measuring these
results over time may lead the "adequate redundancy" to become
higher over time.
Justified Redundancy:
Traditionally, network operators would be much less worried about
energy use than about the possibility that the network would have
brownout or backout outages - thus the measuring will help better
balance the "adequate redundancy" against the related energy use,
resulting in turn in "justified redundancy": a balance between
costs and benefits, with energy use as well as material use as a
clear cost factor.
Please note that "justified redundancy" may be higher than "adequate
redundancy" when we manage to organize the redundancy in a multi-
layer fashion: (1) capacity that is "always on" and always uses
energy; (2) capacity that can turn on quickly when needed; (and
possibly (3) capacity that is "on the shelf" (even in the box) but
ready to be deployed quickly when needed.)
6.4. How Much are Performance and Quality of Experience Compromised?
The fields of performance and quality of experience have the benefit
of significant study and standardization of metrics. As with
resiliency, a degradation of performance and Quality of Service
parameters, such as bandwidth, latency, jitter, etc., can be observed
and measured, as a variation of sustainability metrics. The relative
slopes of improvement of each goal would hint as to where the balance
lies.
6.5. End-to-End Sustainability
The networking industry is in the starting phases of addressing this
objective. We are seeing a sprinkling of sustainability features
across the networking stack and components of devices, whether it is
on forwarding chips, power supplies, optics, and compute. Many of
those optimizations and features are typically local in nature, and
widely scattered across different elements of a network architecture.
An opportunity for maximizing the positive environmental impact of
these technologies calls for a more cohesive and complementary view
that spans the complete product lifecycle for hardware and software,
as well as how some of these features work in unison.
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For example, features that provide energy saving modes for devices
can be dynamically managed when the network utilization is such that
performance would not significantly suffer. A core router, instead
of becoming obsolete due to the need for higher throughput in the
core, could become a future edge/access router. That is an example
of reuse and repurpose, before recycling. There are benefits of
macro-optimizations by clustering in specific features, versus micro-
optimizing locally without awareness of the network context.
6.6. Attributional and Consequential Models
Many of the subtleties and nuances of the measurement of GHG and
environmental impacts stem from the very important distinction
between attributional and consequential models. Detailed definitions
can be found at [UNEP-LCA].
Attributional:
Also referred to as Allocational models, start by allocating or
attributing quantities (e.g., GHG emissions) to entities (e.g., a
router, a building, a town), and performing comparisons between
the measurements (or estimates) of the quantity by the entities.
Consequential:
Perform the measurement of the quantity by establishing a baseline
scenario (e.g., before feature introduction) and a modified
scenario (e.g., after the feature introduction).
While both models are quite different, they do use the same terms and
frames of references, measures, and language. Without explicit
clarifications, they are prone to confusion.
For example, measuring the carbon footprint attributed to a batch
process or a workload based on its energy efficiency would not
consider that the hardware is still there running. When is it most
effective to charge battery-powered devices, during the night when
there's less load, or during the day when there's solar energy? In
other words, if a person who commutes by train to their office five
days a week starts working from home two days a week, there could be
an attributional reduction of GHG emissions, yet the train still
continues running equally. However, if that person commutes by
combustion-engine car alone, the consequences are different.
Considering the attributional versus consequential distinction, there
are some implications and a potential corollaries:
* For an environmental-impact analysis, it is critical to explicitly
cite the model used, as well as clearly define the boundary.
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* The activities that we embark upon as internetworking and protocol
designers - including the ones targeting reduction of negative
environmental impacts - have an energy footprint of themselves.
* "Do no harm" in the context of improving sustainability of
networks is to look beyond bounded attributions and consider (both
intended and unintended) consequences.
6.7. The Role of Network Management and Orchestration
Deployment and operational aspects play a critical role in making
networks more sustainable. A detailed explanation of that role, the
associated challenges, as well as an outline of solution approaches
is provided in [I-D.irtf-nmrg-green-ps]. Here are some areas in
which network management can help make networks more sustainable; for
a more extensive treatment, please refer to that document.
Dimensioning:
Networks should be deployed and configured with sufficient
capacity to serve their intended purpose. At the same time,
overprovisioning and providing too many resources should be
avoided, as this results in waste and unnecessary environmental
impact. Network management can facilitate proper dimensioning of
networks by providing the methods and tools that allow to assess
network usage, determine required capacities, identify trends to
allow to proactively accommodate traffic growth and new services.
Network Optimization:
Network management applications can help solve difficult network
optimization problems involving multiple parameters, multiple and
sometimes conflicting objectives, and mitigation of tradeoffs.
Network optimization examples include maximization of utilization
or of aggregate QoE scores, minimization of the possibility of SLA
violations with a given amount of network resources, or
optimization of the cost of configured paths. Network metrics
related to sustainability are another set of parameters that can
be optimized.
Rapid Discovery and Provisioning Schemes:
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One of the biggest potential opportunities in reducing
environmental impact of networks concerns the ability to power
resources such as equipment or line cards down when they are
momentarily not needed due to swings in traffic demands. In
general, this involves fully automated management control loops
with very short time scales. Network management can enable such
schemes, involving algorithms that determine and control the rapid
de- and re-commissioning of networking resources, as well as the
necessary control protocols that facilitate aspects such as rapid
resource discovery, reprovisioning, or reconvergence of management
state.
6.7.1. Metrics for Sustainability
A sustainability quantification framework is paramount for
understanding the sustainability posture of a system, as well as its
potential for aid in sustainability outcomes.
7. Sustainability Requirements and Phases
The considerations and advice for sustainability described in the
"Sustainability Considerations - How Will the Natural Environment be
Impacted?" and "Sustainability Guidelines for Protocol and Network
Designers and Implementers" sections and their associated goals
cannot always be achieved at the same time and we expect the
following high level phases:
1. Visibility: In this phase we focus on the measurement and
collection of metrics.
2. Insights and Recommendations: In this phase we focus on deriving
insights and providing recommendations that can be acted upon
manually over large time scales.
3. Self-Optimization via Automation: In this phase we build
awareness into the systems to automatically recognize
opportunities for improvement and implement them.
7.1. Phase 1: Visibility
Visibility represents collecting and organizing data in a standard
vendor agnostic manner. The first step in improving our
environmental impact is to actually measure it in a clear and
consistent manner. The IETF, IRTF and the IAB have a long history of
work in this field, and this has greatly helped with the
instrumentation of network equipment in collecting metrics for
network management, performance, and troubleshooting. On the
environmental-impact side though, there has been a proliferation of a
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wide variety of vendor extensions based on these standards. Without
a common definition of metrics across the industry and widespread
adoption we will be left with ill-defined, potentially redundant,
proprietary, or even contradicting metrics. Similarly, we also need
to work on standard telemetry for collecting these metrics so that
interoperability can be achieved in multi-vendor networks.
7.2. Phase 2: Insights and Recommendations
Once the metrics have been collected, categorized, and aggregated in
a common format, it would be straightforward to visualize these
metrics and allow consumers to draw insights into their GHG and
energy impact. The visualizations could take the form of high-level
dashboards that provide aggregate metrics and potentially some form
of maturity continuum. We think this can be accomplished using
reference implementations of the standards developed in "Phase 1:
Visibility". We do expect vendors and other open projects to
customize this and incorporate specific features. This will allow
identifying sources of environmental impact and address any potential
issues through operational changes, creation of best-practices, and
changes towards a greener, more environmentally friendly equipment,
software, platforms, applications, and protocols.
7.3. Phase 3: Self-optimization and Automation
Manually making changes as mentioned in "Phase 2: Insights and
Recommendations" works for changes needed on large timescales but
does not scale to improvements on smaller scales (i.e., it is
impractical in many levels for an operator to be looking at a
dashboard monitoring usage and making changes in real-time 24x7).
There is a need to provision some amount of self-awareness into the
network itself, at various layers, so that it can recognize
opportunities for improvement and make those changes and measure the
effects by closing the loop. The goals of the consumers can be
stated in a declarative fashion, and the networks can continually use
mechanisms such as machine learning (ML), deep learning (DL), and
artificial intelligence (AI) with an additional goal to optimize for
improvements in the environmental impact. These include, for
example:
* Discovery and advertisement of networking characteristics that
have either direct or indirect environmental impact,
* greener networking protocols that can move traffic onto more
energy efficient paths, directing topological graphs to optimize
environmental impacts, and
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* protocols that can instruct equipment to move under-utilized links
and devices into low-energy modes.
7.3.1. Cycle of Phases
The three phases run in an iterative fashion, such that after phases
1, 2, and 3 are completed for an interation, there will be an added
awareness of what (else) to collect back to phase 1.
Further, sustainability-aware self-optimization is something to
explore in Autonomic Networking.
8. Sustainability Guidelines for Protocol and Network Designers and
Implementers
This section renders the Sustainability Considerations into specific
guidelines and advice for the design and development of networking
technologies.
These specific items are labeled so as to follow and reference as a
check-list.
a. General:
The section title "Sustainability Considerations" should be used
to detail the environmental-impact implications of protocols,
architectures, and Internet technologies.
a.1. For each of the items covered, explicitly state the
"boundary of analysis" considered. For example, this can
include a scope, time boundary, or lifecycle phases.
a.2. Consider attributional versus consequential analysis
methods, explaining environmental impact benefits.
a.3. Clearly state the units used for each magnitude in every
analysis (e.g., gCO2e/KWh.)
b. Network Management:
Several areas of network management have direct relationship with
sustainability.
b.1. Metrics:
Instrument equipment, network elements, and networks with a
set of relevant and meaningful metrics that provide
visibility into sustainability and environmental-impact
attributes (e.g., power and energy consumption.) This is
the foundation for any mechanisms to improve and optimize
sustainability.
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b.2. Managed Elements:
Facilitate, extend, and enrich the manageability of network
elements and sub-elements which have environmental impact,
such as Power Supplies. For example, provide visibility
into sourced power, e.g. energy mix, and allow to account
for the "dirtiness" of power being consumed to obtain a
truer picture of sustainability than can be gained by
visibility into power consumption alone.
c. Energy Management:
Minimizing energy consumption is a critical consideration in
making networks more sustainable. Minimizing energy consumption
typically comes also with important economic side benefits
associated with reducing operational expenses and making network
providers more competitive.
To facilitate energy efficiency schemes, designers of networking
devices and protocols should examine and consider the following
considerations:
c.1. Energy linearity. In many cases, the amount of power drawn
by a device is not in linear proportion to the volume of
traffic that is passed. Instead, energy consumption when
idle generally accounts for a very significant percentage
of the energy consumption when under full load. The
implication of this is that the volume of traffic by itself
is of relative consequence to energy consumption, as long
as the volume does not get to the point where additional
equipment needs to be added to the network to handle peak
loads.
c.2. Power saving modes. Similarly, many devices and resources
support power saving modes that can be entered when idled.
Similarly, during periods of exceedingly low traffic, some
links may support downspeeding associated with energy
savings. As a result, a big opportunity for energy savings
involves schemes in which resources are temporarily put
into power saving modes, including almost shut-down, at
times when they are not needed.
c.3. Chattiness of protocols. For a given protocol, what are
the message exchange patterns? does the protocol rely on
periodic updates or heartbeat messages? Could such message
patterns result in preventing links or nodes from going to
sleep (absent other communications), and in such a case,
would an alternative pattern be feasible?
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c.4. Exploiting burstiness versus smoothening of traffic. Is it
feasible to design the protocol in such a way that traffic
is sent with a smoother traffic pattern with lower traffic
volumes that are sent continuously, as opposed to a way
that traffic is bulked up and then sent in one fell swoop?
c.5. Rapid discovery and convergence. Does the protocol involve
the exchange of state and information about other systems?
In that case, how can the protocol be designed in such that
any such information can be discovered quickly and protocol
synchronization reconverged efficiently? Does the protocol
design support stateful schemes that might accelerate this?
In cases where there is a possibility of nodes going to
sleep, the associated overhead of going offline and coming
back online should be minimized. By shortening the time
interval needed to go offline and come back online, it
might be possible to have enter sleep mode in situations
where it would otherwise not be feasible.
c.6. Encoding schemes. How much computational effort goes into
encoding and decoding? Assess the tradeoff between
encoding efficiency and computational effort, which directs
into carbon for cycles to perform coding operations.
d. Carbon Awareness:
See the definition in Section 2.
d.1. Consider Carbon Intensity (CI) / Emission Factor (EF) as an
attribute. For example, CI is used to optimize for lower-
carbon sources of electrical energy (e.g., using
renewables.) Prioritizing electricity use when carbon
intensity is low is a target, and, for that, this attribute
needs to be accessed or advertised.
d.2. Consider embodied emissions (i.e., embedded carbon) with
any new product. For example, a new generation of
networking device might significantly improve energy
efficiency, and a replacement migration would include the
embedded emissions (of producing and transporting the new
product as well as disposing of the old one), and hence
there's a break-even point (BEP).
e. Beyond Carbon:
Characterize and note full-spectrum environmental impacts, beyond
GHG emissions, and into water usage, raw materials usage,
circularity in supply chain, repurpose, reuse, and recycle, etc.
e.1. WIP
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e.2. WIP
9. Conclusion
The pre-eminent message in this document is to elevate the need and
sense of urgency of including sustainability considerations in our
protocol and system design, and to provide editors with a
sustainability lexicon, definitions, and priorities to carry out that
task. As an added benefit, by including sustainability
considerations, it will be possible to optimize for not only
performance parameters but also sustainability ones, through
respective trade-offs in our protocols and systems.
We also envision that on top of minimizing the environmental impact
of our technologies and helping consumers identify and reduce the
environmental impact of their use, we can also make a positive impact
on other systems. E.g., use our technologies to choose greener and
more efficient sources of power, control HVAC systems efficiently,
etc.
9.1. Call to Action
The intention of this document is multifaceted: establish definitions
and a lexicon for sustainability, characterize environmental
implications of internetworking technologies, and provide specific
guidelines for designers and implementors.
Making these objectives actionable involves:
1. Familiarize yourself with the terms defined in Section 2,
2. understand the sustainability considerations (Section 3 through
Section 7) and their implications to protocol and architecture,
and
3. consider, qualify, quantify, and explain the specific guidelines
in Section 8 as you develop protocols, extensions, and
architectures.
10. Security Considerations
Sustainable practices offer many environmental, economic, and social
benefits, and security is a route to sustainability rather than a
hurdle to clear.
The creation of sustainability features for an element or a system
should not weaken or compromise their security posture, nor should
it increase the surface of attack or create attack vectors.
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- Sustainability metrics and data models ought to describe how to
secure the sustainability data exposed and surfaced through
telemetry.
- Sustainability control capabilities, as for example for power
management, should consider potential attacks leveraging those
controls. Setting a device on low-power or power-save modes
during peak traffic can be a denial-of-service attack vector,
negatively impacting end-to-end services.
The development of security features should, in turn, balance the
environmental impact and sustainability considerations detailed in
this document.
- Computational increase on cryptographic operations can result
in higher power use. Since generally the increase of energy
required is not linear with the increase of computational
complexity, there's a desire to satisfy security requirements
while minimizing environmental impact.
- Proof-of-Work schemes' and AI models' energy consumption also
grows non-linearly as a function of the precision achieved. In
these, perfect is the enemy of good, and bounding precision
through specifications supports sustainable compute
considerations.
11. Acknowledgements and Contributions
The subject of sustainability considerations for internetworking sits
in the intersection of several disciplines, benefiting from the
collaboration of diverse educational, experiential, and exposure
backgrounds. The authors are not only grateful but also inspired by
the open collaboration and expertise of many individuals, including:
* Maarten Botterman provided text on network redundancy, and
definitions for justified redundancy balancing adequate
redundancy.
* Dom Robinson shared ideas and text on attributional and
consequential methods, in turn inspired by a post from Chris
Adams.
* Michael Welzl provided a very comprehensive and critical review of
the complete document, and highlighted several fixes and
improvements.
12. Informative References
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Authors' Addresses
Carlos Pignataro (editor)
North Carolina State University
United States of America
Email: cpignata@gmail.com, cmpignat@ncsu.edu
Ali Rezaki
Nokia
Germany
Email: ali.rezaki@nokia.com
Suresh Krishnan
Cisco Systems, Inc.
United States of America
Email: sureshk@cisco.com
Hesham ElBakoury
Independent Consultant
United States of America
Email: helbakoury@gmail.com
Alexander Clemm
Futurewei
2220 Central Expressway
Santa Clara, CA 95050
United States of America
Email: ludwig@clemm.org
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