Internet DRAFT - 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
                                                            H. ElBakoury
                                                  Independent Consultant
                                                                A. Clemm
                                                         24 January 2024

           Sustainability Considerations for Internetworking


   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

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

   Internet-Drafts are working documents of the Internet Engineering
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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

   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

   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.

      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

   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.

      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

      *  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.

      Global warming potential, is the potential impact of GHGs on
      climate change, measured in CO2e.

      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.

      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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      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,

   *  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

   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

   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

   An important corollary is that KV enablers can be used to derive
   technological requirements, KPIs and advancements to maximize key

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

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

   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:

                      | Router 1 |------------+
                      +----------+            |
                       | | | | |         +----------+
                       | | | | |         | Router 3 |
                       | | | | |         +----------+
                      +----------+            |
                      | Router 2 |------------+

       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

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].

      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.

      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.

      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

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

   *  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

   This section renders the Sustainability Considerations into specific
   guidelines and advice for the design and development of networking

   These specific items are labeled so as to follow and reference as a

   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

       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

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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

       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

       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,

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,

   3.  consider, qualify, quantify, and explain the specific guidelines
       in Section 8 as you develop protocols, extensions, and

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

      -  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

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

   *  Dom Robinson shared ideas and text on attributional and
      consequential methods, in turn inspired by a post from Chris

   *  Michael Welzl provided a very comprehensive and critical review of
      the complete document, and highlighted several fixes and

12.  Informative References

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              Clemm, A., Westphal, C., Tantsura, J., Ciavaglia, L.,
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              ITU, "Digital technologies to achieve the UN SDGs", 2023,

              Wikström, G., Schuler Scott, A., Mesogiti, I., Stoica, R.,
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   [Planet-B] Azote for Stockholm Resilience Centre, based on analysis
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   [RFC8403]  Geib, R., Ed., Filsfils, C., Pignataro, C., Ed., and N.
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Authors' Addresses

   Carlos Pignataro (editor)
   North Carolina State University
   United States of America

   Ali Rezaki

   Suresh Krishnan
   Cisco Systems, Inc.
   United States of America

   Hesham ElBakoury
   Independent Consultant
   United States of America

   Alexander Clemm
   2220 Central Expressway
   Santa Clara,  CA 95050
   United States of America

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