Internet DRAFT - draft-cx-green-ps
draft-cx-green-ps
Network Working Group A. Clemm
Internet-Draft C. Westphal
Intended status: Informational Futurewei
Expires: 14 September 2023 J. Tantsura
Microsoft
L. Ciavaglia
Nokia
M-P. Odini
13 March 2023
Challenges and Opportunities in Management for Green Networking
draft-cx-green-ps-02
Abstract
Reducing technology's carbon footprint is one of the big challenges
of our age. Networks are an enabler of applications that reduce this
footprint, but also contribute to this footprint substantially
themselves. Many of the biggest opportunities to reduce this
footprint may not be management or even networking specific, for
instance general power efficiency gains in hardware or deployment of
equipment in more energy-efficient buildings. However, methods to
make networking technology itself "greener" and in particular to
manage networks in ways that reduces their carbon footprint without
impacting their utility also need to be explored. This document
outlines a corresponding set of opportunities, along with associated
research challenges, for networking technology in general and
management technology in particular to become "greener" and reduce
network carbon footprint.
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
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 14 September 2023.
Clemm, et al. Expires 14 September 2023 [Page 1]
Internet-Draft Chall-Ops-Green March 2023
Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
extracted from this document must include Revised BSD License text as
described in Section 4.e of the Trust Legal Provisions and are
provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Definitions and Acronyms . . . . . . . . . . . . . . . . . . 6
3. Contributors to Network Energy Consumption . . . . . . . . . 7
3.1. Power Consumption Characteristics . . . . . . . . . . . . 7
3.2. Dimensioning for Peak Usage . . . . . . . . . . . . . . . 8
4. Challenges and Opportunities - Equipment Level . . . . . . . 9
4.1. Hardware and Manufacturing . . . . . . . . . . . . . . . 9
4.2. Visibility and Instrumentation . . . . . . . . . . . . . 10
5. Challenges and Opportunities - Protocol Level . . . . . . . . 11
5.1. Protocol Enablers for Carbon Footprint Optimization
Mechanisms . . . . . . . . . . . . . . . . . . . . . . . 12
5.2. Protocol Optimization . . . . . . . . . . . . . . . . . . 13
5.3. Data Volume Reduction . . . . . . . . . . . . . . . . . . 14
5.4. Network Addressing . . . . . . . . . . . . . . . . . . . 15
6. Challenges and Opportunities - Network Level . . . . . . . . 16
6.1. Network Optimization and Energy/Carbon/Pollution-Aware
Networking . . . . . . . . . . . . . . . . . . . . . . . 16
6.2. Assessing Carbon Footprint and Network-Level
Instrumentation . . . . . . . . . . . . . . . . . . . . . 17
6.3. Convergence Schemes . . . . . . . . . . . . . . . . . . . 18
7. Challenges and Opportunities - Architecture Level . . . . . . 19
8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 21
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 21
10. Security Considerations . . . . . . . . . . . . . . . . . . . 21
11. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 22
12. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 22
13. Informative References . . . . . . . . . . . . . . . . . . . 22
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 26
Clemm, et al. Expires 14 September 2023 [Page 2]
Internet-Draft Chall-Ops-Green March 2023
1. Introduction
Climate change and the need to curb greenhouse emissions have been
recognized by the United Nations and by most governments as one of
the big challenges of our time. As a result, improving energy
efficiency and reducing power consumption are becoming of increasing
importance for society and for many industries. The networking
industry is no exception.
Arguably, networks can already be considered "green" technology in
that networks enable many applications that allow users and whole
industries to save energy and become more sustainable in a
significant way. For example, it allows (at least to an extent) to
replace travel with teleconferencing; it enables many employees to
work from home and "telecommute," thus reducing the need for actual
commute; IoT applications that facilitate automated monitoring and
control from remote sites help make agriculture more sustainable by
minimizing the application of resources such as water and fertilizer;
networked smart buildings allow for greater energy optimization and
sparser use of lighting and HVAC (heating, ventilation, air
conditioning) than their non-networked not-so-smart counterparts.
The IETF has recently initiated a reflection on the energy cost of
hosting meetings three times a year (see for instance
https://www.ietf.org/blog/towards-a-net-zero-ietf/). It conducted a
study of the carbon emissions of a typical meeting, and found out
that 99% of the emissions were due to the air travel. In the same
vein, [framework] compared an in-person with a virtual meeting and
found a reduction in energy of 66% for a virtual meeting. These
findings confirm that networking technology can reduce emissions when
acting as virtual substitution for physical events.
That said, networks themselves consume significant amounts of energy.
Therefore, the networking industry has an important role to play in
meeting sustainability goals not just by enabling others to reduce
their reliance on energy, but by also reducing its own. Future
networking advances will increasingly need to focus on becoming more
energy-efficient and reducing carbon footprint, both for economic
reasons and for reasons of corporate responsibility. This shift has
already begun and sustainability is already becoming an important
concern for network providers. In some cases such as in the context
of networked data centers, the ability to procure enough energy
becomes a bottleneck prohibiting further growth and greater
sustainability thus becomes a business necessity.
For example, in its annual report, Telefónica reports that in 2021,
its network's energy consumption per PB of data amounted to 54MWh
[telefonica2021]. This rate has has been dramatically decreasing (a
Clemm, et al. Expires 14 September 2023 [Page 3]
Internet-Draft Chall-Ops-Green March 2023
seven-fold factor over six years) although gains in efficiency are
being offset by simultaneous growth in data volume. In the same
report, it is stated as an important corporate goal to continue on
that trajectory and aggressively reduce overall carbon emissions
further.
Perhaps the most obvious gains in sustainability can be made with
regards to improving the efficiency with which networks utilize
power, reducing the amount of energy that is required to provide
communication services. However, for a holistic approach other
aspects need to be considered as well. Perhaps most importantly,
carbon footprint is determined not by it power consumption alone.
The sustainability of power sources needs to be taken into account as
well. A deployment that includes devices that are less energy-
efficient but that are powered by a sustainable energy source can
arguably be considered "greener" than a deployment that includes
highly-efficient device that are powered by Diesel generators. In
fact, in the same Telefónica report, extensive reliance on renewable
energy sources is emphasized.
Similarly, deployments can take other environmental factors into
account that affect carbon footprint. For example, deployments in
which factors such as the need for cooling are reduced will be
considered greener than deployments where this is not the case.
Examples include deployments in cooler natural surroundings (e.g. in
colder climates) where that is an option. Finally, manufacturing and
recycling of networking equipment are also part of the sustainability
equation, as the production itself consumes energy and results in a
carbon cost embedded as part of the device itself. Extending the
lifetime of equipment may in many cases be preferable over replacing
it earlier with equipment that is slightly more energy-efficient but
that requires the embedded carbon cost to be amortized over a much
shorter period of time.
From a technical perspective, multiple vectors along which networks
can be made "greener" should be considered:
* At the equipment level. Perhaps the most promising vector for
improving networking sustainability concerns the network equipment
itself. At the most fundamental level, networks (even softwarized
ones) involve appliances, i.e. equipment that relies on electrical
power to perform its function. However, beyond making those
appliances merely more energy-efficient, there are other important
ways in which equipment can help networks become greener. This
includes aspects such as support for port power saving modes
allowing to reduce power consumption for resources that are not
fully utilized, but also management instrumentation that allows to
precisely monitor power usage at different levels of granularity.
Clemm, et al. Expires 14 September 2023 [Page 4]
Internet-Draft Chall-Ops-Green March 2023
This enables (for example) controller applications that aim to
optimize energy usage across the network. (As a side note, the
term "device", as used in the context of this draft, is used to
refer to networking equipment. We are not taking into
consideration end-user devices and endpoints such as mobile phones
or computing equipment.)
* At the protocol level. Energy-efficiency and greenness are
aspects that are rarely considered when designing network
protocols. This suggests that there may be plenty of untapped
potential. Some aspects involve designing protocols in ways that
reduce the need for redundant or wasteful transmission of data to
allow not only for better network utilization, but greater goodput
per unit of energy being consumed. Techniques might include
approaches that reduce the "header tax" incurred by payloads as
well as methods resulting in the reduction of wasteful
retransmissions. Likewise, aspects such as restructuring
addresses in ways that allow to minimize the size of lookup tables
and associated memory sizes and their energy use can play a role
as well. Another role of protocols concerns the enabling of
functionality to improve energy efficiency at the network level,
such as discovery protocols that allow for quick adaptation to
network components being taken dynamically into and out of service
depending on network conditions, as well as protocols that can
assist with functions such as the collection of energy telemetry
data from the network.
* At the network level. Perhaps the greatest opportunities to
realize power savings exist at the level of the network as whole.
For example, optimizing energy efficiency may involve directing
traffic in such a way that it allows for isolation of equipment
that may at the moment not be needed so that it could be powered
down or brought into power-saving mode. By the same token,
traffic should be directed in a way that requires bringing
additional equipment online or out of power-saving mode in cases
where alternative traffic paths are available for which the
incremental energy cost would amount to zero. Likewise, some
networking devices may be rated less "green" and more power-
intensive than others or powered by less-sustainable energy
sources. Their use might be avoided unless required to meet peak
capacity demands. Generally, incremental carbon emissions can be
viewed as a cost metric that networks should strive to minimize
and consider as part of routing and of network path optimization.
* At the architecture level. The current network architecture
supports a wide range of applications, but does not take into
account energy efficiency as one of its design parameters. One
can argue that the most energy efficient shift of the last two
Clemm, et al. Expires 14 September 2023 [Page 5]
Internet-Draft Chall-Ops-Green March 2023
decades has been the deployment of Content Delivery Network
overlays: while these were set up to reduce latency and minimize
bandwidth consumption, from a network perspective, retrieving the
content from a local cache is also much greener. What other
architectural shifts can produce energy consumption reduction?
We believe that network standardization organizations in general, and
IETF in particular, can make important contributions to each of these
vectors. In this document, we will therefore explore each of those
vectors in further detail and for each point out specific challenges
for IETF. As our starting point, we borrow some material from a
prior paper, [GreenNet22]. For this document, this material has been
both expanded (for example, in terms of some of the opportunities)
and pruned (for example, in terms of background on prior scholarly
work). In addition, this document focuses on and attempts to
articulate specific challenges relating to work that could be
championed by the IETF to make a difference.
2. Definitions and Acronyms
Below you find acronyms used in this draft:
Carbon footprint: as used in this document, the amount of carbon
emissions associated with the use or deployment of technology,
usually directly correlated with the associated energy
consumption.
CDN: Content Delivery Network.
CPU: Central Processing Unit, that is the main processor in a
server.
DC: Data Center.
FCT: Flow Completion Time.
HVAC: Heating, Ventilation, Air Conditioning.
ICN: Information Centric Network.
IGP: Interior Gateway Protocol.
IPU: Infrastructure Processing Units.
LEO: Low Earth Orbit.
LPM: Longest Prefix Match, a method to look up prefixes in a
forwarding element.
Clemm, et al. Expires 14 September 2023 [Page 6]
Internet-Draft Chall-Ops-Green March 2023
MPLS: Multi-Path Label Switching
MTU: Maximum Transmission Unit, the largest packet size that can
be transmitted over a network.
NIC: Network Interface Card.
QoS, QoE: Quality of Service, Quality of Experience.
QUIC: Quick UDP Internet Connections.
SDN: Software-Defined Networking.
TCP: Transport Control Crotocol.
TE: Traffic Engineering.
WAN: Wide Area Network.
3. Contributors to Network Energy Consumption
Carbon footprint and, with it, greenhouse gas emissions are
determined by a number of factors. A main factor is network energy
consumption, as the energy consumed can be considered a proxy for the
burning of fuels required for corresponding power generation.
Network energy consumption by itself does not tell the whole story,
as it does not take the sustainability of energy sources and energy
mix into account. Likewise, there are other factors such as hidden
carbon cost reflecting the carbon footprint expended in manufacturing
of networking hardware. Nonetheless, network energy consumption is
an excellent predictor for carbon footprint and its reduction key to
sustainable solutions. Exploring possibilities to improve energy
efficiency is hence a key factor for greener, more sustainable, less
carbon-intensive networks.
For this, it is important to understand which aspects contribute to
power consumption the most and hence where the greatest potential not
just for power savings but also sustainability improvements lies.
3.1. Power Consumption Characteristics
Power is ultimately drawn from devices. The power consumption of the
device can be divided into the consumption of the core device - the
backplane and CPU, if you will - as well as additional consumption
incurred per port and line card. Furthermore it is important to
understand the difference between power consumption when a resource
is idling versus when it is under load. This helps to understand the
incremental cost of additional transmission versus the initial cost
Clemm, et al. Expires 14 September 2023 [Page 7]
Internet-Draft Chall-Ops-Green March 2023
of transmission.
In typical networking devices, only roughly half of the energy
consumption is associated with the data plane [bolla2011energy]. An
idle base system typically consumes more than half of the power over
the same system running at full load [chabarek08], [cervero19].
Generally, the cost of sending the first bit is very high, as it
requires powering up a device, port, etc. The incremental cost of
transmission of additional bits (beyond the first) is many orders of
magnitude lower. Likewise, the incremental cost of incremental CPU
and memory needed to process additional packets becomes fairly
negligible. This means that a device's power consumption does not
increase linearly with the volume of forwarded traffic. Instead, it
resembles more of a step function in which power consumption stays
roughly the same up to a certain volume of traffic, followed by a
sudden jump when when additional resources need to be procured to
support a higher volume of traffic. By the same token, generally
speaking it is more energy-efficient to transmit a large volume of
data in one burst (and turning off the interface when idling),
instead of continuously transmitting at a lower rate. In that sense
it can be the duration of the transmission that dominates the energy
consumption, not the actual data rate.
3.2. Dimensioning for Peak Usage
The implications on green networking from an energy-savings
standpoint are significant: Potentially the largest gains can be made
when network resources can effectively be taken off the grid (i.e.
isolated and removed from service so they can be powered down while
not needed). Likewise, for applications where this is possible, it
may be desirable to replace continuous traffic at low data rates with
traffic that is sent in burst at high data rates, in order to
potentially maximize the time during which resources can be idled.
At the same time, any non-idle resources should be utilized to the
greatest extent possible as the incremental energy cost is
negligible. Of course, this needs to occur while still taking other
operational goals into consideration, such as protection against
failures (allowing for readily-available redundancy and spare
capacity in case of failure) and load balancing (for increased
operational robustness). As data transmission needs tend to
fluctuate wildly and occur in bursts, any optimization schemes need
to be highly adaptable and allow for very short control loops.
As a result, emphasis needs to be given to technology that allows to
(for example) (at the device level) exercise very efficient and rapid
discovery, monitoring, and control of networking resources so that
they can be dynamically be taken offline or back into service,
Clemm, et al. Expires 14 September 2023 [Page 8]
Internet-Draft Chall-Ops-Green March 2023
without (at the network level) requiring extensive convergence of
state across the network or recalculation of routes and other
optimization problems, and (at the network equipment level) support
rapid power cycle and initialization schemes.
4. Challenges and Opportunities - Equipment Level
We are categorizing challenges and opportunities to improve
sustainability at the network equipment level along the following
lines:
* Hardware and manufacturing. Related opportunities are arguably
among the most obvious and perhaps "largest". However, solutions
here may lie largely outside IETF's scope.
* Visibility and instrumentation. Instrumenting equipment to
provide visibility into how they consume energy is key to
management solutions and control loops to facilitate optimization
schemes.
4.1. Hardware and Manufacturing
Perhaps the most obvious opportunities to make networking technology
more energy efficient exist at the equipment level. After all,
networking involves physical equipment to receive and transmit data.
Making such equipment more power efficient, have it dissipate less
heat to consume less energy and reduce the need for cooling, making
it eco-friendly to deploy, sourcing sustainable materials and
facilitating recycling of equipment at the end of its life-cycle all
contribute to making networks greener. More specific and unique to
networking are schemes to reduce energy usage of transmission
technology from wireless (antennas) to optical (lasers).
One critical aspect of the energy cost of networking is the cost to
manufacture and deploy the networking equipment. This is outside of
the scope of this document: we only consider the energy cost of
running the network, as this is where the IETF can play a role.
However, a holistic approach would include into this the embedded
energy that is included in the networking equipment. One aspect for
the IETF may be to consider impact of deploying new protocols on the
rate of obsolescence of the equipment. For instance, incremental
approaches that do not require to replace equipment right away - or
even extend the lifetime of deployed equipment - would have a lower
energy footprint. This is one important benefit also of technologies
such as Software-Defined Networking and Network Function
Virtualization, as they may allow support of new networking features
through software updates without requiring hardware replacements.
Clemm, et al. Expires 14 September 2023 [Page 9]
Internet-Draft Chall-Ops-Green March 2023
An attempt compute not only the energy of running a network, but also
the energy embedded into manufacturing the equipment is described in
[emergy] . This is denoted by "emergy", a portmanteau for embedded
energy. [junkyard] Likewise, an approach to recycling equipment and a
proof of concept using old cell phones recycled into a "junkyard"
data center are described in [emergy].
4.2. Visibility and Instrumentation
Beyond "first-order" opportunities as outlined in the previous
subsection, network equipment just as importantly plays an important
role to enable and support green networking at other levels. Of
prime importance is the equipment's ability to provide visibility to
management and control plane into its current energy usage. Such
visibility enables control loops for energy optimization schemes,
allowing applications to obtain feedback regarding the energy
implications of their actions, from setting up paths across the
network that require the least incremental amount of energy to
quantifying metrics related to energy cost used to optimize
forwarding decisions.
One prerequisite to such schemes is to have proper instrumentation in
place that allows to monitor current power consumption at the level
of networking devices as a whole, line cards, and individual ports.
Such instrumentation should also allow to assess the energy
efficiency and carbon footprint of the device as a whole. In
addition, it will be desirable to relate this power consumption to
data rates as well as to current traffic, for example, to indicate
current energy consumption relative to interface speeds, as well as
for incremental energy consumption that is expected for incremental
traffic (to aid control schemes that aim to "shave" power off current
services or to minimize the incremental use of power for additional
traffic). This is an area where the current state of the art is
sorely lacking and standardization lags behind. For example, as of
today, standardized YANG data models [RFC7950] for network energy
consumption that can be used in conjunction with management and
control protocols have yet to be defined.
To remedy this situation, an effort to define sets of green
networking metrics is currently under way
[I.D.draft-cx-green-metrics]. An agreed set of such metrics will
provide the basis for further steps such as the implementation of
corresponding data models as part of management and control
instrumentation.
Instrumentation should also take into account the possibility of
virtualization, introducing layers of indirection to assess the
actual energy usage. For example, virtualized networking functions
Clemm, et al. Expires 14 September 2023 [Page 10]
Internet-Draft Chall-Ops-Green March 2023
could be hosted on containers or virtual machines which are hosted on
a CPU in a data center instead of a regular network appliance such as
a router or a switch, leading to very different power consumption
characteristics. For example, a data center CPU could be more power
efficient and consume power more proportionally to actual CPU load.
Instrumentation needs to reflect these facts and facilitate
attributing power consumption in a correct manner.
Beyond monitoring and providing visibility into power consumption,
control knobs are needed to configure energy saving policies. For
instance, power saving modes are common in endpoints (such as mobile
phones or notebook computers) but sorely lacking in networking
equipment.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances:
* Equipment instrumentation advances for improved energy-awareness;
definition and standardization of granular management information.
* Virtualized energy and pollution metrics and assessment of their
effectiveness in solutions that optimize carbon footprint also in
virtualized environments (including SDN, network slicing, network
function virtualization, etc.).
* Certification and compliance assessment methods that ensure that
green instrumentation cannot be manipulated to give false and
misleading data.
* Methods that allow to account for energy mix powering equipment,
to facilitate solutions that optimize pollution and carbon
footprint beyond mere energy efficiency [Hossain2019].
5. Challenges and Opportunities - Protocol Level
There are several opportunities to improve network sustainability at
the protocol level. We characterize them along three main
categories: protocols that enable carbon footprint optimization
schemes at the network level, protocols designed to optimize data
transmission rates under energy considerations, and protocols
designed to reduce the volume of data to be transmitted. A fourth
category concerns aspects related to network addressing schemes.
Clemm, et al. Expires 14 September 2023 [Page 11]
Internet-Draft Chall-Ops-Green March 2023
5.1. Protocol Enablers for Carbon Footprint Optimization Mechanisms
As will be discussed in Section Section 6, energy- and pollution-
aware schemes can help improve network sustainability but require
awareness of related data. To facilitate such schemes, protocols are
needed that are able to discover what links are available along with
their energy efficiency. For instance, links may be turned off in
order to save energy, and turned back on based upon the elasticity of
the demand. Protocols should be devised to discover when this
happens, and to have a view of the topology that is consistent with
frequent topology updates due to power cycling of the network
resources.
Also, protocols are required to quickly converge onto an energy-
efficient path once a new topology is created by turning links on/
off. Current routing protocols may provide for fast recovery in the
case of failure. However, failures are hopefully relatively rare
events, while we expect an energy efficient network to aggressively
try to turn off links.
Some mechanism is needed to present to the management layer a view of
the network that identifies opportunities to turn resources off
(routers/links) while still providing an acceptable level of Quality
of Experience (QoE) to the users. This gets more complex as the
level of QoE shifts from the current Best Effort delivery model to
more sophisticated mechanisms with, for instance, latency, bandwidth
or reliability guarantees.
Similarly, schemes might be devised in which links across paths with
a favorable energy mix are preferred over other paths. This implies
that the discovery of topology should be able support corresponding
parameters. More generally speaking, any mechanism that provides
applications with network visibility is a candidate for
scrutinization as to whether it should be extended to provide support
for sustainability-related parameters.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances:
* Protocol advances to enable rapidly taking down, bring back
online, and discover availability and power saving status of
networking resources while minimizing the need for reconvergence
and propagation of state.
* Assess which protocols could be extended with energy- and
sustainability-related parameters in ways that would enable
"greener" networking solutions, and exploring those solutions.
Clemm, et al. Expires 14 September 2023 [Page 12]
Internet-Draft Chall-Ops-Green March 2023
5.2. Protocol Optimization
The second category involves designing protocols in such a way that
the rate of transmission is chosen to maximize energy efficiency.
For example, Traffic Engineering (TE) can be manipulated to impact
the rate adaptation mechanism [ren2018jordan]. By choosing where to
send the traffic, TE can artificially congest links so as to trigger
rate adaptation and therefore reduce the total amount of traffic.
Most TE systems attempt to minimize Maximal Link Utilization (MLU)
but energy saving mechanisms could decide to do the opposite
(maximize minimal link utilization) and attempt to turn off some
resources to save power.
Another example is to set up the proper rate of transmission to
minimize the flow completion time (FCT) so as to enable opportunities
to turn off links. In a wireless context, [TradeOff] studies how
setting the proper initial value for the congestion window can reduce
the FCT and therefore allow the equipment to go faster into a low-
energy mode. By sending the data faster, the energy cost can be
significantly reduced. This is a simple proof of concept, but
protocols that allow for turning links into a low-power mode by
transmitting the data over shorter periods could be designed for
other types of networks beyond WiFi access. This should be done
carefully: in the limit, a high rate of transmission over a short
period of time may create bursts that the network would need to
accommodate, with all attendant complications of bursty traffic. We
conjecture there is a sweet spot between trying to complete flows
faster while controlling for burstiness in the network. It is
probably advisable to attempt to send traffic paced yet in bulk
rather than spread out over multiple round trips. This is an area of
worthwhile exploration.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances:
* Protocol advances that allow greater control over traffic pacing
to account for fluctuations in carbon cost, i.e. control knobs to
"bulk up" transmission over short periods or to smoothen it out
over longer periods.
* Protocol advances that allow to optimize link utilization
according to different goals and strategies (including maximizing
minimal link utilization vs minimizing maximal link utilization,
etc).
* Assessments of the carbon impact of such strategies.
Clemm, et al. Expires 14 September 2023 [Page 13]
Internet-Draft Chall-Ops-Green March 2023
5.3. Data Volume Reduction
The first category involves designing protocols in such a way that
they reduce the volume of data that needs to be transmitted for any
given purpose. Loosely speaking, by reducing this volume, more
traffic can be served by the same amount of networking
infrastructure, hence reducing overall energy consumption.
Possibilities here include protocols that avoid unnecessary
retransmissions. At the application layer, protocols may also use
coding mechanisms that encode information close to the Shannon limit.
Currently, most of the traffic over the Internet consists of video
streaming and encoders for video are already quite efficient and keep
improving all the time, resulting in energy savings as one of many
advantages (of course being offset by increasingly higher
resolution). However, it is not clear that the extra work to achieve
higher compression ratios for the payloads results in a net energy
gain: what is saved over the network may be offset by the
compression/decompression effort. Further research on this aspect is
necessary.
At the transport protocol layer, TCP and to some extent QUIC react to
congestion by dropping packets. This is a highly energy inefficient
method to signal congestion, since the network has to wait one RTT to
be aware that the congestion has occurred, and since the effort to
transmit the packet from the source up until it is dropped ends up
being wasted. This calls for new transport protocols that react to
congestion without dropping packets. ECN[RFC2481] is a possible
solution, however not widely deployed. DC-TCP [alizadeh2010DCTCP] is
tuned for Data Centers, L4S is an attempt to port similar
functionality to the Internet [I-D.ietf-tsvwg-l4s-arch]. Qualitative
Communication [QUAL] [westphal2021qualitative] allows the nodes to
react to congestion by dropping only some of the data in the packet,
thereby only partially wasting the resource consumed by transmitted
the packet up to this point. Novel transport protocols for the WAN
can ensure that no energy is wasted transmitting packets that will be
eventually dropped.
Another solution to reduce the bandwidth of network protocols by
reducing their header tax, for example applying header compression.
An example in IETF is [RFC3095]. Again, reducing protocol header
size saves energy to forward packets, but at the cost of maintaining
a state for compression/decompression, plus computing these
operations. The gain from such protocol optimization further depends
on the application and whether it sends packets with large payloads
close to the MTU (the header tax and any savings here are very
limited), or whether it sends packets with very small payload size
(making the header tax more pronounced and savings more significant).
Clemm, et al. Expires 14 September 2023 [Page 14]
Internet-Draft Chall-Ops-Green March 2023
An alternative to reducing the amount of protocol data is to design
routing protocols that are more efficient to process at each node.
For instance, path based forwarding/labels such as MPLS [RFC3031]
facilitate the next hop look-up, thereby reducing the energy
consumption. It is unclear if some state at router to speed up look
up is more energy efficient that "no state + lookup" that is more
computationally intensive. Other methods to speed up a next-hop
lookup include geographic routing (e.g. [herzen2011PIE]). Some
network protocols could be designed to reduce the next hop look-up
computation at a router. It is unclear if Longest Prefix Match (LPM)
is efficient from an energy point of view or if constitutes a
significant energy burden for the operation of a router.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances in this space:
* Assessments of energy-related tradeoffs regarding protocol design
space and tradeoffs, such as maintaining state versus more compact
encodings or extra computation for transcodings versus larger data
volume.
* Protocol advances for improving the ratio of goodput to throughput
and to reduce waste: reduction in header tax, in protocol
verbosity, in need for retransmissions, improvements in coding,
etc.
5.4. Network Addressing
There are other ways to shave off energy usage from networks. One
example concerns network addressing. Address tables can get very
large, resulting in large forwarding tables that require considerable
amount of memory, in addition to large amounts of state needing to be
maintained and synchronized. From an energy footprint perspective,
both can be considered wasteful and offer opportunities for
improvement. At the protocol level, rethinking how addresses are
structured can allow for flexible addressing schemes that can be
exploited in network deployments that are less energy-intensive by
design. This can be complemented by supporting clever address
allocation schemes that minimize the number of required forwarding
entries as part of deployments.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances in this space:
* Devise methods to assess the magnitude of the carbon footprint
that is associated with addressing schemes.
Clemm, et al. Expires 14 September 2023 [Page 15]
Internet-Draft Chall-Ops-Green March 2023
* Devise methods to improve addressing schemes, as well as address
assignment schemes, to minimize their footprint.
6. Challenges and Opportunities - Network Level
6.1. Network Optimization and Energy/Carbon/Pollution-Aware Networking
Networks have been optimized for many years under many criteria, for
example to optimize (maximize) network utilization and to optimize
(minimize) cost. Hence, it is straighforward to add optimization for
"greenness" (including energy efficiency, power consumption, carbon
footprint) as important criteria.
This includes assessing the carbon footprints of paths and optimizing
those paths so that overall footprint is minimized, then applying
techniques such as path-aware networking or segment routing [RFC8402]
to steer traffic along those paths. It also includes aspects such as
considering the incremental carbon footprint in routing decisions.
Optimizing cost has a long tradition in networking; many of the
existing mechanisms can be leveraged for greener networking simply by
introducing carbon footprint as a cost factor. Low-hanging fruit
include the inclusion of carbon-related parameters as a cost
parameter in control planes, whether distributed (e.g. IGP) or
conceptually centralized via SDN controllers.
Other opportunities concern adding carbon-awareness to dynamic path
selection schemes. This is sometimes also referred to as "energy-
aware networking" (respectively "pollution-aware networking"
[Hossain2019] or "carbon-aware networking", when carbon footprint
related parameters beyond pure energy consumption are taken into
account). Again, considerable energy savings can potentially be
realized by taking resources offline (e.g. putting them into power-
saving or hibernation mode) when they are not currently needed under
current network demand and load conditions. Therefore, weaning such
resources from traffic becomes an important consideration for energy-
efficient traffic steering. This contrasts and indeed conflicts with
existing schemes that typically aim to create redundancy and load-
balance traffic across a network to achieve even resource
utilization. This usually occurs for important reasons, such as
making networks more resilient, optimizing service levels, and
increasing fairness. One of the big challenges hence concerns how
resource weaning schemes to realize energy savings can be
accommodated while preventing the cannibalization of other important
goals, counteracting other established mechanisms, and avoiding
destabilization of the network.
Clemm, et al. Expires 14 September 2023 [Page 16]
Internet-Draft Chall-Ops-Green March 2023
An opportunity may lie in making a distinction between "energy modes"
of different domains. For instance, in a highly trafficked core, the
energy challenge is to transmit the traffic efficiently. The amount
of traffic is relatively fluid (due to multiplexing of multiple
sessions) and the traffic is predictable. In this case, there is no
need to optimize on a per session basis nor even at a short time
scale. In the access networks connecting to that core, though, there
are opportunites for this fast convergence: traffic is much more
bursty, less predictable and the network should be able to be more
reactive. Other domains such as DCs may have also more variable
workloads and different traffic patterns.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances in this space:
* Devise methods for carbon-aware traffic steering and routing;
treat carbon footprint as a traffic cost metric to optimize.
* Apply ML and AI methods to optimize networks for carbon footprint;
assess applicability of game theoretic approaches.
* Articulate and, as applicable, moderate tradeoffs between carbon
awareness and other operational goals such as robustness and
redundancy.
* Extend control-plane protocols with carbon-related parameters.
* Consider security issues imposed by greater energy awareness, to
minimize the new attack surfaces that would allow an adversary to
turn off resources or to waste energy.
6.2. Assessing Carbon Footprint and Network-Level Instrumentation
As an important prerequisite to capture many of the opportunities
outlined in Section 6.1, good abstractions (and corresponding
instrumentation) that allow to easily assess energy cost and carbon
footprint will be required. These abstractions need to account for
not only for the energy cost associated with packet forwarding across
a given path, but related cost for processing, for memory, for
maintaining of state, to result in a holistic picture.
Optimization of carbon footprint involves in many cases trade-offs
that involve not only packet forwarding but also aspects such as
keeping state, caching data, or running computations at the edge
instead of elsewhere. (Note: there may be a differential in running
a computation at an edge server vs. at an hyperscale DC. The latter
is often better optimized than the latter.) Likewise, other aspects
of carbon footprint beyond mere energy-intensity should be
Clemm, et al. Expires 14 September 2023 [Page 17]
Internet-Draft Chall-Ops-Green March 2023
considered. For instance, some network segments may be powered by
more sustainable energy sources than others, and some network
equipment may be more environmentally-friendly to build, deploy and
recycle, all of which can be reflected in abstractions to consider.
Assessing carbon footprint at the network level requires
instrumentation that associates that footprint not just with
individual devices (as outline in Section 4.2 but relates it also to
concepts that are meaningful at the network level, i.e. to flows and
to paths. For example, it will be useful to provide visibility into
the carbon intensity of a path: Can the carbon cost of traffic
transmitted over the path be aggregated? Does the path include
outliers, i.e. segments with equipment with a particularly poor
carbon footprint?
Similarly, how can the carbon cost of a flow be assessed? That might
serve many purposes beyond network optimization, from the option to
introduce green billing and charging schemes to the ability to raise
carbon awareness by end users.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances in this space:
* Devise methods to assess, to estimate, to predict carbon-intensity
of paths.
* Devise methods to account for carbon footprint of flows and
networking services.
6.3. Convergence Schemes
One set of challenges of carbon-aware networking concerns the fact
that many schemes result in much greater dynamicity and continuous
change in the network as resources may be getting steered away from
(when possible) and then leveraged again (when necessary) in rapid
succession. This imposes significant stress on convergence schemes
that results in challenges to the scalability of solutions and their
ability to perform in a fast-enough manner. Network-wide convergence
imposes high cost and incurs significant delay and is hence not
susceptible to such schemes. In order to mitigate this problem,
mechanisms should be investigate that do not require convergence
beyond the vicinity of the affected network device. Especially in
cases where central network controllers are involved that are
responsible for aspects such as configuration of paths and the
positioning of network functions and that aim for global
optimization, the impact of churn needs to be minimized. This means
that, for example, (re-) discovery and update schemes need to be
simplified and extensive recalculation e.g. of routes and paths based
Clemm, et al. Expires 14 September 2023 [Page 18]
Internet-Draft Chall-Ops-Green March 2023
on the current energy state of the network needs to be avoided.
Challenges and opportunities for IETF-led advances in this space
include:
* Protocols that facilitate rapid convergence (per section
Section 5.1).
* Investigate methods that mitigate effects of churn, including
methods that maintain memory or state as well as methods relying
on prediction, inference, and interpolation.
7. Challenges and Opportunities - Architecture Level
Another possibility to improve network energy efficiency is to
organize networks in a way that they can best serve important
applications so as to minimize energy consumption. Examples include
retrieval of content or remote computation. This allows to minimize
the amount of communication that needs to take place in the first
place, although energy savings within the network may at least in
part be offset by additional energy consumption elsewhere. The
following are some examples that suggest that it may be worthwhile
reconsidering the ways in which networks are architected to minimize
their carbon footprint.
For example, Content Delivery Networks (CDNs) have reduced the energy
expenditure of the Internet by downloading content near the users.
The content is sent only a few times over the WAN, and then is served
locally. This shifts the energy consumption from networking to
storage. Further methods can reduce the energy usage even more
[bianco2016energy][mathew2011energy][islam2012evaluating]. Whether
overall energy savings are net positive depends on the actual
deployment, but from the network operator's perspective, at least it
shifts the energy bill away from the network to the CDN operator.
While CDNs operate as an overlay, another architecture has been
proposed to provide the CDN features directly in the network, namely
Information Centric Networks [ahlgren2012survey], studied as well in
the IRTF ICNRG. This however shifts the energy consumption back to
the network operator and requires some power-hungy hardware, such as
chips for larger name look-ups and memory for the in-network cache.
As a result, it is unclear if there is an actual energy gain from the
dissemination and retrieval of content within in-network caches.
Fog computing and placing intelligence at the edge are other
architectural directions for reducing the amount of energy that is
spent on packet forwarding and in the network. There again, the
trade-off is between performing computation in a an energy-optimized
Clemm, et al. Expires 14 September 2023 [Page 19]
Internet-Draft Chall-Ops-Green March 2023
data center at very large scale, but requiring transmission of
significant volumes of data across many nodes and long distances,
versus performing computational tasks at the edge where the energy
may not be used as efficiently (less multiplexing of resources, and
smaller sites are inherently less efficient due to their smaller
scale) but the amount of long-distance network traffic is
significantly reduced. Softwarization, containers, microservices are
direct enablers for such architectures, and the deployment of
programmable network infrastructure (as for instance Infrastructure
Processing Units - IPUs or smartNICs that offload some computations
from the CPU onto the NIC) will help its realization. However, the
power consumption characteristics of CPUs are different from those of
NPUs, another aspect to be considered in conjunction with
virtualization.
Other possibilities concern taking economic aspects into
consideration impact, such as providing incentives to users of
networking services in order to minimize energy consumption and
emission impact. An example for this is given in
[wolf2014choicenet], which could be expanded to include energy
incentives.
Other approaches consider performing a late binding of data and
functions to be performed on the data [krol2017NFaaS]. The COIN
Research Group in IRTF focuses on similar issues. Jointly optimizing
for the total energy cost, taking into account networking and
computing (and the different energy cost of computing in an
hyperscale DC vs an edge node) is still an area of open research.
In summary, rethinking of the overall network (and networked
application) architecture can be an opportunity to significantly
reduce the energy cost at the network layer, for example by
performing tasks that involve massive communications closer to the
user. To what extend these shifts result in a net reduction of
carbon footprint is an important question that requires further
analysis on a case-by-case basis.
The following summarizes some challenges and opportunities that can
provide the basis for IETF-led advances in this space:
* Investigate organization of networking architecture for important
classes of applications (examples: content delivery, right-placing
of computational intelligence, industrial operations and control,
massively distributed machine learning and AI) to optimize green
foot print and holistic approaches to trade off carbon footprint
between forwarding, storage, and computation.
Clemm, et al. Expires 14 September 2023 [Page 20]
Internet-Draft Chall-Ops-Green March 2023
* Models to assess and compare alternatives in providing networked
services, e.g. assess carbon impact relative to alternatives where
as to where to perform compute, what information to cache, and
what communication exchanges to conduct.
8. Conclusions
How to make networks "greener" and reduce their carbon footprint is
an important problem for the networking industry to address, both for
societal and for economic reasons. This document has highlighted a
number of the technical challenges and opportunities in that regard.
Of those, perhaps the key challenge to address right away concerns
the ability to expose at a fine granularity the energy impact of any
networking actions. Providing visibility into this will enable many
approaches to come towards a solution. It will be key to
implementing optimization via control loops that allow to assess the
energy impact of decisiont taken. It will also help to answer
questions such as: is caching - with the associated storage energy -
better than retransmitting from a different server - with the
associated networking cost? Is compression more energy-efficient
once factoring the computation cost of compression vs transmitting
uncompressed data? Which compression scheme is more energy
efficient? Is energy saving of computing at an efficient hyperscale
DC compensated by the networking cost to reach that DC? Is the
overhead of gathering and transmitting fine-grained energy telemetry
data offset by the total energy gain by ways of better decisions that
this data enables? Is transmitting data to a Low Earth Orbit (LEO)
satellite constellation compensated by the fact that once in the
constellation, the networking is fueled on solar energy? Is the
energy cost of sending rockets to place routers in Low Earth Orbit
amortized over time?
Determining where the sweet spots are and optimizing networks along
those lines will be a key towards making networks "greener". We
expect to see significant advances across these areas and believe
that IETF has an important role to play in facilitating this.
9. IANA Considerations
This document does not have any IANA requests.
10. Security Considerations
Security considerations may appear to be orthogonal to green
networking considerations. However, there are a number of important
caveats.
Clemm, et al. Expires 14 September 2023 [Page 21]
Internet-Draft Chall-Ops-Green March 2023
Security vulnerabilities of networks may manifest themselves in
compromised energy efficiency. For example, attackers could aim at
increasing energy consumption in order to drive up attack victims'
energy bill. Specific vulnerabilities will depend on the particular
mechanisms. For example, in the case of monitoring energy
consumption data, tampering with such data might result in
compromised energy optimization control loops. Hence any mechanisms
to instrument and monitor the network for such data need to be
properly secured to ensure authenticity.
In some cases there are inherent tradeoffs between security and
maximal energy efficiency that might otherwise be achieved. An
example is encryption, which requires additional computation for
encryption and decyption activities and security handshakes, in
addition to the need to send more traffic than necessitated by the
entropy of the actual data stream. Likewise, mechanisms that allow
to turn resources on or off could become a target for attackers.
Energy consumption can be used to create covert channels, which is a
security risk for information leakage. For instance, the temperature
of an element can be used to create a Thermal Covert Channel[TCC], or
the reading/sharing of the measured energy consumption can be abused
to create a covert channel (see for instance [DRAM] or [NewClass]).
Power information may be used to create side-channel attacks. For
instance, [SideChannel] provides a review of 20 years of study on
this topic. Any new parameters to consider in protocol designs or in
measurements is susceptible to create such covert or side channel and
this should be taken into account while designing energy efficient
protocols.
11. Contributors
Michael Welzl, University of Oslo, michawe@ifi.uio.no
12. Acknowledgments
We thank Dave Oran for providing the information regarding covert
channels using energy measurements. Additional acknowledgments will
be added at a later stage.
13. Informative References
[ahlgren2012survey]
Ahlgren, B., Dannewitz, C., Imbrenda, C., Kutscher, D.,
and B. Ohlman, "A survey of information-centric
networking", IEEE Communications Magazine Vol.50 No.7,
2012.
Clemm, et al. Expires 14 September 2023 [Page 22]
Internet-Draft Chall-Ops-Green March 2023
[alizadeh2010DCTCP]
Alizadeh, M., Greenberg, A., Maltz, D., Padhye, J., Patel,
P., Prabhakar, B., Sengupta, S., and M. Sridharan, "Data
Center TCP (DCTCP)", ACM SIGCOMM pp.63-74, 2010.
[bianco2016energy]
Bianco, A., Mashayekhi, R., and M. Meo, "Energy
consumption for data distribution in content delivery
networks", IEEE International Conference on Communications
(ICC) pp.1-6, 2016.
[bolla2011energy]
Bolla, R., Bruschi, R., Davoli, F., and F. Cucchietti,
"Energy Efficiency in the Future Internet: A Survey of
Existing Approaches and Trends in Energy-Aware Fixed
Network Infrastructures", IEEE Communications Surveys and
Tutorials Vol.13 No.2, pp.223-244, 2011.
[cervero19]
Cervero, A. G., Chincoli, M., Dittmann, L., Fischer, A.,
and A. Garcia, "Green Wired Networks", Wiley Journal on
Large-Scale Distributed Systems and Energy
Efficiency pp.41-80, 2019.
[chabarek08]
Chabarek, J., Sommers, J., Barford, P., Tsiang, D., and S.
Wright, "Power awareness in network design and routing",
IEEE Infocom pp.457-465, 2008.
[DRAM] Paiva, T. B., Navaridas, J., and R. Terada, "Robust Covert
Channels Based on DRAM Power Consumption", In book:
Information Security (pp.319-338) , 2019.
[emergy] Raghavan, B. and J. Ma, "The Energy and Emergy of the
Internet", ACM HotNets , 2011.
[framework]
Faber, G., "A framework to estimate emissions from virtual
conferences", International Journal of Environmental
Studies, 78:4, 608-623 , 2021.
[GreenNet22]
Clemm, A. and C. Westphal, "Challenges and Opportunities
in Green Networking", 1st International Workshop on
Network Energy Efficiency in the Softwarization Era IEEE
NetSoft 2022, June 2022.
Clemm, et al. Expires 14 September 2023 [Page 23]
Internet-Draft Chall-Ops-Green March 2023
[herzen2011PIE]
Herzen, J., Westphal, C., and P. Thiran, "Scalable routing
easy as PIE: A practical isometric embedding protocol",
19th IEEE International Conference on Network Protocols
(ICNP) pp.49-58, 2011.
[Hossain2019]
Hossain, M., Georges, J., Rondeau, E., and T. Divoux,
"Energy, Carbon and Renewable Energy: Candidate Metrics
for Green-Aware Routing?", DOI: 10.3390/s19132901,
Sensors Vol. 19 No. 3, June 2019,
<https://ieeexplore.ieee.org/document/6779082>.
[I-D.ietf-tsvwg-l4s-arch]
Briscoe, B., De Schepper, K., Bagnulo, M., and G. White,
"Low Latency, Low Loss, and Scalable Throughput (L4S)
Internet Service: Architecture", Work in Progress,
Internet-Draft, draft-ietf-tsvwg-l4s-arch-20, 29 August
2022, <https://datatracker.ietf.org/doc/html/draft-ietf-
tsvwg-l4s-arch-20>.
[I.D.draft-cx-green-metrics]
Clemm, A., Dong, L., Mirsky, G., Ciavaglia, L., Tantsura,
J., and M. Odini, "Green Networking Metrics", March 2023.
[islam2012evaluating]
Islam, S. U. and J. Pierson, "Evaluating Energy
Consumption in CDN Servers", Proceedings of the Second
International Conference on ICT as Key Technology against
Global Warming pp.64-78, 2012.
[junkyard] Switzer, J., Kastner, R., and P. Pannuto, "Architecture of
a Junkyard Datacenter", arXiv:2110.06870v1, October 2021 ,
2021.
[krol2017NFaaS]
Krol, M. and I. Psaras, "NFaaS: Named Function as a
Service", ACM SIGCOMM ICN Conference , 2017.
[mathew2011energy]
Mathew, V., Sitaraman, R., and P. Shenoy, "Energy-Aware
Load Balancing in Content Delivery Networks", CoRR
http://arxiv.org/abs/1109.5641 , 2011.
[NewClass] Khatamifard, S. K., Wang, L., Kose, S., and U. R.
Karpuzcu, "A New Class of Covert Channels Exploiting Power
Management Vulnerabilities", IEEE Computer Architecture
Letters , 2018.
Clemm, et al. Expires 14 September 2023 [Page 24]
Internet-Draft Chall-Ops-Green March 2023
[QUAL] Li, R., Makhijani, K., Yousefi, H., Westphal, C., Xong,
L., Wauters, T., and F. D. Turck, "A framework for
Qualitative Communications using Big Packet Protocol",
Proceedings ACM Sigcomm Workshop On Networking For
Emerging Applications And Technologies pp.22-28, 2019.
[ren2018jordan]
Ren, J., Ren, K., Westphal, C., Wang, J., Wang, J., Song,
T., Liu, S., and J. Wang, "JORDAN: A Novel Traffic
Engineering Algorithm for Dynamic Adaptive Streaming over
HTTP", IEEE International Conference on Computing,
Networking and Communications (ICNC) pp.581-587, 2018.
[RFC2481] Ramakrishnan, K. and S. Floyd, "A Proposal to add Explicit
Congestion Notification (ECN) to IP", RFC 2481,
DOI 10.17487/RFC2481, January 1999,
<https://www.rfc-editor.org/info/rfc2481>.
[RFC3031] Rosen, E., Viswanathan, A., and R. Callon, "Multiprotocol
Label Switching Architecture", RFC 3031,
DOI 10.17487/RFC3031, January 2001,
<https://www.rfc-editor.org/info/rfc3031>.
[RFC3095] Bormann, C., Burmeister, C., Degermark, M., Fukushima, H.,
Hannu, H., Jonsson, L., Hakenberg, R., Koren, T., Le, K.,
Liu, Z., Martensson, A., Miyazaki, A., Svanbro, K.,
Wiebke, T., Yoshimura, T., and H. Zheng, "RObust Header
Compression (ROHC): Framework and four profiles: RTP, UDP,
ESP, and uncompressed", RFC 3095, DOI 10.17487/RFC3095,
July 2001, <https://www.rfc-editor.org/info/rfc3095>.
[RFC7950] Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
RFC 7950, DOI 10.17487/RFC7950, August 2016,
<https://www.rfc-editor.org/info/rfc7950>.
[RFC8402] Filsfils, C., Ed., Previdi, S., Ed., Ginsberg, L.,
Decraene, B., Litkowski, S., and R. Shakir, "Segment
Routing Architecture", RFC 8402, DOI 10.17487/RFC8402,
July 2018, <https://www.rfc-editor.org/info/rfc8402>.
[SideChannel]
Randolph, M. and W. Diehl, "Power Side-Channel Attack
Analysis: A Review of 20 Years of Study for the Layman",
Cryptography 2020, 4, 15 , 2020.
Clemm, et al. Expires 14 September 2023 [Page 25]
Internet-Draft Chall-Ops-Green March 2023
[TCC] Rahimi, P., Singh, A. K., and X. Wang, "Selective Noise
Based Power Efficient and Effective Countermeasure Against
Thermal Covert Channel Attacks in Multi-Core Systems",
Journal on Low Power Electronics and Applications , 2022.
[telefonica2021]
Telefonica, "Telefonica Consolidated Annual Report 2021.",
2021.
[TradeOff] Welzl, M., "Not a Trade-Off: On the Wi-Fi Energy
Efficiency of Effective Internet Congestion Control",
IEEE/IFIP WONS , 2022.
[westphal2021qualitative]
Westphal, C., He, D., Makhijani, K., and R. Li,
"Qualitative Communications for Augmented Reality and
Virtual Reality", 22nd IEEE International Conference on
High Performance Switching and Routing (HPSR) pp.1-6,
2021.
[wolf2014choicenet]
Tilman, W., Griffioen, J., Calvert, L., Dutta, R.,
Rouskas, G., Baldin, I., and A. Nagurney, "ChoiceNet:
Toward an Economy Plane for the Internet", SIGCOMM
Computer Communciations Review Vol.44 No.3, July 2014.
Authors' Addresses
Alexander Clemm
Futurewei
2330 Central Expressway
Santa Clara,, CA 95050
United States of America
Email: ludwig@clemm.org
Cedric Westphal
Futurewei
Email: cedric.westphal@futurewei.com
Jeff Tantsura
Microsoft
Email: jefftant.ietf@gmail.com
Laurent Ciavaglia
Nokia
Clemm, et al. Expires 14 September 2023 [Page 26]
Internet-Draft Chall-Ops-Green March 2023
Email: laurent.ciavaglia@nokia.com
Marie-Paule Odini
Email: mp.odini@orange.fr
Clemm, et al. Expires 14 September 2023 [Page 27]
