Challenges and Opportunities in Green Networking
draft-cx-green-ps-00
The information below is for an old version of the document.
| Document | Type |
This is an older version of an Internet-Draft whose latest revision state is "Replaced".
|
|
|---|---|---|---|
| Authors | Alexander Clemm , Cedric Westphal , Jeff Tantsura , Laurent Ciavaglia , Marie-Paule Odini | ||
| Last updated | 2022-07-11 | ||
| Replaced by | draft-irtf-nmrg-green-ps | ||
| RFC stream | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | I-D Exists | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
draft-cx-green-ps-00
Network Working Group A. Clemm
Internet-Draft C. Westphal
Intended status: Informational Futurewei
Expires: January 12, 2023 J. Tantsura
Microsoft
L. Ciavaglia
Rakuten Mobile
M-P. Odini
July 11, 2022
Challenges and Opportunities in Green Networking
draft-cx-green-ps-00
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. The biggest opportunities to reduce the energy footprint
may not be networking specific, for instance general power efficiency
gains in hardware or hosting of equipment in more cooling-efficient
buildings. Yet methods to make networking technology itself
"greener" also need to be explored. This document outlines a
corresponding set of opportunities, along with associated research
challenges, for reducing this footprint and reducing network energy
demand.
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 January 12, 2023.
Clemm, et al. Expires January 12, 2023 [Page 1]
Internet-Draft July 2022
Copyright Notice
Copyright (c) 2022 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 Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definitions and Acronyms . . . . . . . . . . . . . . . . . . 5
3. Contributors to Network Energy Consumption . . . . . . . . . 5
4. Challenges and Opportunities - Equipment Level . . . . . . . 6
5. Challenges and Opportunities - Protocol Level . . . . . . . . 7
5.1. Data Volume Reduction . . . . . . . . . . . . . . . . . . 8
5.2. Traffic Adaptation . . . . . . . . . . . . . . . . . . . 9
5.3. Enabling Network Energy Saving Mechanisms . . . . . . . . 9
5.4. Network Addressing . . . . . . . . . . . . . . . . . . . 10
6. Challenges and Opportunities - Network Level . . . . . . . . 10
7. Challenges and Opportunities - Architecture Level . . . . . . 12
8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 13
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 15
10. Security Considerations . . . . . . . . . . . . . . . . . . . 15
11. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 15
12. Informative References (TBD) . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 18
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
Clemm, et al. Expires January 12, 2023 [Page 2]
Internet-Draft July 2022
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.
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, Telefonica reports that in 2020,
its network's energy consumption per PB of data amounted to 78MWh
[telefonica2020]. This rate has has been dramatically decreasing (a
five-fold factor over five 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 reduce overall carbon emissions by 70% over the
next 5 years.
From a technical perspective, multiple vectors along which networks
can be made "greener" should be considered:
o 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 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 instrumentation that allows to precisely
monitor power usage at different levels of granularity, enabling
(for example) controllers 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
Clemm, et al. Expires January 12, 2023 [Page 3]
Internet-Draft July 2022
equipment. We are not taking into consideration end-user devices
and endpoints such as mobile phones or computing equipment.)
o 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 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.
o 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 more power-intensive than others whose
use might be avoided unless required to meet peak capacity
demands. Generally, incremental power consumption can be viewed
as a cost metric that networks should strive to minimize and
consider as part of routing and of network path optimization.
o 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
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?
Clemm, et al. Expires January 12, 2023 [Page 4]
Internet-Draft July 2022
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 there explore each of those
vectors in further detail and for each point out specific challenges
for IETF.
It should be noted that this document borrows heavily from material
from a prior paper, [GreenNet22]. 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, unlike the prior paper, this document focuses on and
attempts to articulate specific challenges as related to work that
could be championed by the IETF.
2. Definitions and Acronyms
TBD
3. Contributors to Network Energy Consumption
When exploring possibilities to improve energy efficiency, it is
important to understand which aspects contribute to power consumption
the most and hence where the greatest potential for power savings
lies.
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
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]. This
means that a device's power consumption increases not linearly with
the volume of forwarded traffic but resembles more of a step
function. Generally, the cost of the first bit is very high, as it
requires powering up a device, port, etc. The 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. 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
Clemm, et al. Expires January 12, 2023 [Page 5]
Internet-Draft July 2022
lower rate. In that sense it can be the duration of the transmission
that dominates the energy consumption, not the actual data rate.
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,
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
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).
Beyond such "first-order" opportunities, 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
Clemm, et al. Expires January 12, 2023 [Page 6]
Internet-Draft July 2022
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 would 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, no corresponding standardized YANG data models [RFC7950] for
network energy consumption that can be used in conjunction with
management and control protocols have been defined.
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
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.
5. Challenges and Opportunities - Protocol Level
There are several opportunities for energy savings at the protocol
level. We characterize them along three main categories: protocols
designed to reduce the volume of data to be transmitted; protocols
designed to optimize data transmission rates under energy
considerations; and protocols that enable energy optimization schemes
Clemm, et al. Expires January 12, 2023 [Page 7]
Internet-Draft July 2022
at the network level. A fourth category, "other", is used to capture
any other aspects not easily categorized into the other three.
5.1. 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 the Data Center. 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. We believe there is a need for novel transport protocols for
the WAN that ensures 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
Clemm, et al. Expires January 12, 2023 [Page 8]
Internet-Draft July 2022
limited), or whether it sends packets with very small payload size
(making the header tax more pronounced and savings more significant).
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 inefficient from an energy point of view, or if it is a
significant energy budget cost for the operation of a router.
5.2. Traffic Adaptation
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 minimial link utilization) and attempt to turn off some
resources to save power.
5.3. Enabling Network Energy Saving Mechanisms
Novel protocols are also needed in two dimensions: to discover what
links are available and/or energy efficient. 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
Clemm, et al. Expires January 12, 2023 [Page 9]
Internet-Draft July 2022
(routers/links) while still providing some decent 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.
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.
6. Challenges and Opportunities - Network Level
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 energy usage 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 energy footprint as a cost factor. Low-hanging fruit
include the inclusion of energy-related parameters as a cost
parameter in control planes, whether distributed (e.g. IGP) or
conceptually centralized via SDN controllers.
Other opportunities concern adding energy-awareness to dynamic path
selection schemes, requiring corresponding instrumentation as
mentioned earlier. 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
Clemm, et al. Expires January 12, 2023 [Page 10]
Internet-Draft July 2022
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.
As an important prerequisite to capture many of those opportunities,
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 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.
A related set of challenges concerns the fact that such 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. The impact will in all likelihood needs to be
mechanisms 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, extensive recalculation
e.g. of routes and paths based on the current energy state of the
network needs to be avoided.
Clemm, et al. Expires January 12, 2023 [Page 11]
Internet-Draft July 2022
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.
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 January 12, 2023 [Page 12]
Internet-Draft July 2022
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.
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
some of the technical challenges and opportunities in that regard,
for example:
o Equipment instrumentation advances for improved energy-awareness,
definition and standardization of granular management information;
Clemm, et al. Expires January 12, 2023 [Page 13]
Internet-Draft July 2022
o Protocol advances for improving the ratio of goodput to throughput
and to reduce waste: reduction in header tax, in protocol
verbosity, improvements in coding, etc.
o 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;
o Network advances to allow to dynamically take resources offline
where feasible while minimizing churn;
o Energy footprint aware traffic steering and routing; carbon
footprint as a traffic cost metric to optimize;
o Reorganization of networking architecture for important classes of
applications (examples: content delivery, right-placing of
computational intelligence) to optimize green foot print and
holistic approaches to trade off carbon footprint between
forwarding, storage, and computation;
o 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;
o Reliability issues for a network that relies on fewer resource
diversity, and with more operational complexity.
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 LEO 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?
Clemm, et al. Expires January 12, 2023 [Page 14]
Internet-Draft July 2022
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.
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.
11. Acknowledgments
Acknowledgments will be added at a later stage.
12. Informative References (TBD)
[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 January 12, 2023 [Page 15]
Internet-Draft July 2022
[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.
[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.
[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.
[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.
Clemm, et al. Expires January 12, 2023 [Page 16]
Internet-Draft July 2022
[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.
[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-E., 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>.
Clemm, et al. Expires January 12, 2023 [Page 17]
Internet-Draft July 2022
[telefonica2020]
Telefonica, "Consolidated Management Report 2020", 2021.
[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
USA
Email: ludwig@clemm.org
Cedric Westphal
Futurewei
Email: cedric.westphal@futurewei.com
Jeff Tantsura
Microsoft
Email: jefftant.ietf@gmail.com
Laurent Ciavaglia
Rakuten Mobile
Email: laurent.ciavaglia@rakuten.com
Marie-Paule Odini
Email: mp.odini@orange.fr
Clemm, et al. Expires January 12, 2023 [Page 18]