Internet Architecture Board (IAB) J. Arkko
Request for Comments: 9075 S. Farrell
Category: Informational M. Kühlewind
ISSN: 2070-1721 C. Perkins
June
July 2021
Report from the IAB COVID-19 Network Impacts Workshop 2020
Abstract
The Coronavirus disease (COVID-19) pandemic caused changes in
Internet user behavior, particularly during the introduction of
initial quarantine and work-from-home arrangements. These behavior
changes drove changes in Internet traffic.
The Internet Architecture Board (IAB) held a workshop to discuss
network impacts of the pandemic on November 9-13, 2020. The workshop
was held to convene interested researchers, network operators,
network management experts, and Internet technologists to share their
experiences. The meeting was held online given the ongoing travel
and contact restrictions at that time.
Note that this document is a report on the proceedings of the
workshop. The views and positions documented in this report are
those of the workshop participants and do not necessarily reflect IAB
views and positions.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Architecture Board (IAB)
and represents information that the IAB has deemed valuable to
provide for permanent record. It represents the consensus of the
Internet Architecture Board (IAB). Documents approved for
publication by the IAB are not candidates for any level of Internet
Standard; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc9075.
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Table of Contents
1. Introduction
2. Scope
3. Workshop Topics and Discussion
3.1. Measurement-Based Observations on Network Traffic Dynamics
3.1.1. Overall Traffic Growth
3.1.2. Changes in Application Use
3.1.3. Mobile Networks and Mobility
3.1.4. A Deeper Look at Interconnections
3.1.5. Cloud Platforms
3.1.6. Last-Mile Congestion
3.1.7. User Behavior
3.2. Operational Practices and Architectural Considerations
3.2.1. Digital Divide
3.2.2. Applications
3.2.3. Observability
3.2.4. Security
3.2.5. Discussion
3.3. Conclusions
4. Feedback on Meeting Format
5. Position Papers
6. Program Committee
7. Informative References
Appendix A. Workshop Participants
IAB Members at the Time of Approval
Acknowledgments
Authors' Addresses
1. Introduction
The Internet Architecture Board (IAB) held a workshop to discuss
network impacts of the COVID-19 pandemic on November 9-13, 2020. The
workshop was held to convene interested researchers, network
operators, network management experts, and Internet technologists to
share their experiences. The meeting was held online given the
ongoing travel and contact restrictions at that time.
COVID-19 has caused changes in user behavior, which in turn drove
changes in Internet traffic. These changes in user behavior appeared
rather abruptly and were significant, in particular during the
introduction of initial quarantine and work-from-home arrangements.
This caused changes in Internet traffic in terms of volume and
location, as well as shifts in the types of applications used. This
shift in traffic and user behavior also created a shift in security
practices as well as attack patterns that made use of the attack
surface, resulting from the shift to working from home in a global
crisis.
An announcement for the workshop was sent out in July 2020 requesting
that interested parties submit position papers to the workshop
program committee. A total of 15 position papers were received from
33 authors in total. The papers are listed in Section 5. In
addition, several other types of contributions and pointers to
existing work were provided. A number of position papers referred to
parallel work being published in measurement-related academic
conferences.
Invitations for the workshop were sent out based on the position
papers and other expressions of interest. On the workshop conference
calls were 46 participants, listed in Appendix A.
The workshop was held over the course of one week and hosted three
sessions covering i) measurements and observations, ii) operational
and security issues, and iii) future consideration and conclusions.
As these three sessions were scheduled on Monday, Wednesday, and
Friday, a positive side effect was that the time in between the
sessions could be used for mailing list discussion and compilation of
additional workshop material.
2. Scope
The COVID-19 pandemic has had a tremendous impact on people's lives
as well as societies and economies around the globe. But it also had
a big impact on networking. With large numbers of people working
from home or otherwise depending on the network for their daily
lives, network traffic volume has surged. Internet service providers
and operators have reported 20% or more traffic growth in a matter of
weeks. Traffic at Internet Exchange Points (IXPs) is similarly on
the rise. Most forms of network traffic have seen an increase, with
conversational multimedia traffic growing, in some cases, by more
than 200%. And user time spent on conferencing services has risen by
an order of magnitude on some conferencing platforms.
In general, the Internet has coped relatively well with this traffic
growth. The situation is not perfect: there have also been some
outages, video quality reduction, and other issues. Nevertheless, it
is interesting to see how the technology, operators, and service
providers have been able to respond to large changes in traffic
patterns.
Understanding what actually happened with Internet traffic is, of
course, interesting in its own right. How that impacted the user
experience or the intended function of the services is equally
interesting. Measurements of and reports on Internet traffic in 2020
are therefore valuable. But it would also be interesting to
understand what types of network management and capacity expansion
actions were taken in general. Anecdotal evidence points to Internet
and service providers tracking how their services are used and, in
many cases, adjusting services to accommodate the new traffic
patterns, from dynamic allocation of computing resources to more
complex changes.
The impacts of this crisis are also a potential opportunity to
understand the impact of traffic shifts and growth more generally to
prepare for future situations -- crises or otherwise -- that impact
networking, or to allow us to adjust the technology to be even better
suited to respond to changes.
The scope of this workshop, based on the call for contributions,
included:
* measurements of traffic changes, user experience and problems,
service performance, and other relevant aspects
* discussion about the behind-the-scenes network management and
expansion activities
* sharing experiences in the fields of general Internet
connectivity, conferencing, media/entertainment, and Internet
infrastructure
* lessons learned on preparedness and operations
* lessons learned on Internet technology and architecture
3. Workshop Topics and Discussion
3.1. Measurement-Based Observations on Network Traffic Dynamics
The workshop started with a focus on measurements. A large portion
of the submitted papers presented and discussed measurement data, and
these submissions provided a good basis for a better understanding of
the situation, covering different angles and aspects of network
traffic and different kinds of networks.
Changes in Internet traffic due to the COVID-19 pandemic affected
different networks in various ways. Yet all networks saw some form
of change, be it a reduction in traffic, an increase in traffic, a
change in workday and weekend diurnal patterns, or a change in
traffic classes. Traffic volume, directionality ratios, and traffic
origins and destinations were radically different than from before
COVID-19.
At a high level, while traffic from home networks increased
significantly, for the traffic in mobile networks different trends
were observed. Either the traffic increased as well -- for instance,
in locations where use of residential ISP services is less common --
traffic decreased as a result of reduced population mobility. This
observed traffic decrease in mobile networks reflected rather the
opposite trend than what was observed in residential ISPs.
While diurnal congestion at interconnect points as well in certain
last-mile networks was reported, mainly in March, no persistent
congestion was observed. Further, a downward trend in download
throughput to certain cloud regions was measured, which can probably
be explained by the increased use of cloud services. This gives
another indication that the scaling of shared resources in the
Internet is working reasonably well enough to handle even larger
changes in traffic as experienced during the first nearly global
lockdown of the COVID-19 pandemic.
3.1.1. Overall Traffic Growth
The global pandemic has significantly accelerated the growth of data
traffic worldwide. Based on the measurement data of one ISP, three
IXPs, a metropolitan educational network, and a mobile operator, it
was observed at the beginning of the workshop [Feldmann2020] that,
overall, the network was able to handle the situation well despite a
significant and sudden increase in the traffic growth rate in March
and April. That is, after the lockdown was implemented in March, a
traffic increase of 15-20% was observed at the ISP as well as at the
three IXPs. This traffic growth, which would typically occur over a
year, took place over a few weeks -- a substantial increase. At DE-
CIX Frankfurt, the world's largest Internet Exchange Point in terms
of data throughput, the year 2020 saw the largest increase in peak
traffic within a single year since the IXP was founded in 1995.
Additionally, mobile traffic has slightly receded. In access
networks, the growth rate of upstream traffic also exceeded the
growth in downstream traffic, reflecting increased adoption and use
of videoconferencing and other remote work and school applications.
Most traffic increases happened outside of pre-pandemic peak hours.
Before the first COVID-19 lockdowns, the main time of use was in the
evening hours during the week, whereas, since March, it has been
spread more equally across the day. That is, the increase in usage
has mainly occurred outside the previous peak usage times (e.g.,
during the day while working from home). This means that, for the
first time, network utilization on weekdays resembled that on
weekends. The effects of the increased traffic volume could easily
be absorbed, either by using existing reserve capacity or by quickly
switching additional bandwidth. This is one reason why the Internet
was able to cope well with the pandemic during the first lockdown
period.
Some of the lockdowns were lifted or relaxed around May 2020. As
people were allowed to resume some of their daily activities outside
of their home again, as expected, there was a decrease in the traffic
observed at the IXPs and the ISP; instead, mobile traffic began to
grow again.
3.1.2. Changes in Application Use
The composition of data traffic has changed since the beginning of
the pandemic: the use of videoconferencing services and virtual
private networks (VPNs) for access to company resources from the home
environment has risen sharply. In ISP and IXP networks, it was
observed [Feldmann2020] that traffic associated with web
conferencing, video, and gaming increased significantly in March 2020
as a result of the increasing user demand for solutions like Zoom or
Microsoft Teams. For example, the relative traffic share of many
"essential" applications like VPN and conferencing tools increased by
more than 200%.
Also, as people spent more hours at home, they tended to watch videos
or play games, thus increasing entertainment traffic demands. At the
same time, the traffic share for other traffic classes decreased
substantially, e.g., traffic related to education, social media, and,
for some periods, content delivery networks (CDNs). In April and
June, web conferencing traffic was still high compared to the pre-
pandemic scenario, while a slight decrease in CDN and social media
traffic was observed. During these months, many people were still
working from home, but restrictions had been lifted or relaxed, which
likely led to an increase in in-person social activities and a
decrease in online social activities.
3.1.2.1. Example Campus Networks
Changes in traffic have been observed at university campus networks
as well, especially due to the necessary adoption of remote teaching.
The Politecnico di Torino (Italy) deployed its in-house solution for
remote teaching, which caused the outgoing traffic to grow by 2.5
times, driven by more than 600 daily online classes. Incoming
traffic instead decreased by a factor of 10 due to the cessation of
any in-person activity. Based on their measurements, this change in
traffic and network usage did not, however, lead to noticeable
performance impairments, nor has significantly poor performance been
observed in students in remote regions of Italy. Outgoing traffic
also increased due to other remote working solutions, such as
collaboration platforms, VPNs, and remote desktops.
Similar changes were observed by measuring REDIMadrid [Feldmann2020],
a European educational and research network that connects 16
independent universities and research centers in the metropolitan
region of Madrid. A drop of up to 55% in traffic volume on working
days during the pandemic was observed. Similar to findings for ISP/
IXP networks, it was observed that working days and weekend days are
becoming more similar in terms of total traffic. The hourly traffic
patterns reveal a traffic increase between 9 pm and 7 am. This could
be due to users working more frequently at unusual times but could
also potentially be caused by overseas students (mainly from Latin
America and East Asia as suggested by the Autonomous System (AS)
numbers from which these connections came) who accessed university
network resources from their home countries.
Given the fact that the users of the academic network (e.g., students
and research staff) had to leave campus as a response to lockdown
measures, the traffic in-and-out (i.e., ingress and egress) ratio
also changed drastically. Prior to the lockdown, the incoming
traffic volume was much larger than the outgoing traffic volume.
This changed to a more balanced ratio. This change of traffic
asymmetry can be explained by the nature of remote work. On the one
hand, users connected to the network services mainly to access
resources, hence the increase in outgoing traffic. On the other
hand, all external (i.e., Internet-based) resources requested during
work were no longer accessed from the educational network but from
the users' homes.
3.1.3. Mobile Networks and Mobility
Mobile network data usage appeared to decline following the
imposition of localized lockdown measures as these reduced typical
levels of mobility and roaming.
[Lutu2020] measured the cellular network of O2 UK to evaluate how the
changes in people's mobility impacted traffic patterns. By analyzing
cellular network signaling information regarding users' device
mobility activity, they observed a decrease of 50% in mobility
(according to different mobility metrics) in the UK during the
lockdown period. As they found no correlation between this reduction
in mobility and the number of confirmed COVID-19 cases, only the
enforced government order was effective in significantly reducing
mobility, and this reduction was more significant in densely
populated urban areas than in rural areas. For London specifically,
it could be observed from the mobile network data that approximately
10% of residents temporarily relocated during the lockdown.
These mobility changes had immediate implications in the traffic
patterns of the cellular network. The downlink data traffic volume
aggregated for all bearers (including conversational voice) decreased
for the entire UK by up to 25% during the lockdown period. This
correlates with the reduction in mobility that was observed
countrywide, which likely resulted in people relying more on
residential broadband Internet access to run download-intensive
applications such as video streaming. The observed decrease in the
radio cell load, with a reduction of approximately 15% across the UK
after the stay-at-home order was enacted, further corroborates the
drop in cellular connectivity usage.
The total uplink data traffic volume, on the other hand, experienced
little change (between -7% and +1.5%) during lockdown. This was
mainly due to the increase of 4G voice traffic (i.e., Voice over LTE
(VoLTE)) across the UK that peaked at 150% after the lockdown
compared to the national median value before the pandemic, thus
compensating for the decrease in data traffic in the uplink.
Finally, it was also observed that mobility changes have a different
impact on network usage in geodemographic area clusters. In densely
populated urban areas, a significantly higher decrease of mobile
network usage (i.e., downlink and uplink traffic volume, radio load,
and active users) was observed compared to rural areas. In the case
of London, this was likely due to the geodemographics of the central
districts, which include many seasonal residents (e.g., tourists) and
business and commercial areas.
3.1.4. A Deeper Look at Interconnections
Traffic at points of network interconnection noticeably increased,
but most operators reacted quickly by rapidly adding additional
capacity [Feldmann2020]. The amount of increase varied, with some
networks that hosted popular applications such as videoconferencing
experiencing traffic growth of several hundred to several thousand
percent. At the IXP level, it was observed that port utilization
increased. This phenomenon is mostly explained by higher traffic
demand from residential users.
Measurements of interconnection links at major US ISPs by the Center
for Applied Internet Data Analysis (CAIDA) and the Massachusetts
Institute of Technology (MIT) found some evidence of diurnal
congestion around the March 2020 time frame [Clark2020], but most of
this congestion disappeared in a few weeks, which suggests that
operators indeed took steps to add capacity or otherwise mitigate the
congestion.
3.1.5. Cloud Platforms
Cloud infrastructure played a key role in supporting bandwidth-
intensive videoconferencing and remote learning tools to practice
social distancing during the COVID-19 pandemic. Network congestion
between cloud platforms and access networks could impact the quality
of experience of these cloud-based applications. CAIDA leveraged
web-based speed test servers to take download and upload throughput
measurements from virtual machines in public cloud platforms to
various access ISPs in the United States [Mok2020].
The key findings included the following:
* Persistent congestion events were not widely observed between
cloud platforms and these networks, particular for large-scale
ISPs, but we could observe large diurnal download throughput
variations in peak hours from some locations to the cloud.
* There was evidence of persistent congestion in the egress
direction to regional ISPs serving suburban areas in the US.
Their users could have suffered from poor video streaming or file
download performance from the cloud.
* The macroscopic analysis over 3 months (June-August 2020) revealed
downward trends in download throughput from ISPs and educational
networks to certain cloud regions. We believe that increased use
of the cloud in the pandemic could be one of the factors that
contributed to the decreased performance.
3.1.6. Last-Mile Congestion
The last mile is the centerpiece of broadband connectivity, where
poor last-mile performance generally translates to poor quality of
experience. In a recent Internet Measurement Conference (IMC '20)
research paper, Fontugne et al. investigated last-mile latency using
traceroute data from Reseaux IP Europeens (RIPE) Atlas probes located
in 646 ASes and looked for recurrent performance degradation
[Fontugne2020-1]. They found that, in normal times, Atlas probes
experience persistent last-mile congestion in only 10% of ASes, but
they recorded 55% more congested ASes during the COVID-19 outbreak.
This deterioration caused by stay-at-home measures is particularly
marked in networks with a very large number of users and in certain
parts of the world. They found Japan to be the most impacted country
in their study, looking specifically at the Nippon Telegraph and
Telephone (NTT) Corporation Open Computer Network (OCN) but noting
similar observations for several Japanese networks, including
Internet Initiative Japan (IIJ) (AS2497).
From mid-2020 onward, however, they observed better performance than
before the pandemic. In Japan, this was partly due to the
deployments originally planned for accommodating the Tokyo Olympics,
and, more generally, it reflects the efforts of network operators to
cope with these exceptional circumstances. The pandemic has
demonstrated that its adaptive design and proficient community can
keep the Internet operational during such unprecedented events.
Also, from the numerous research and operational reports recently
published, the pandemic is apparently shaping a more resilient
Internet; as Nietzsche wrote, "What does not kill me makes me
stronger".
3.1.7. User Behavior
The type of traffic needed by the users also changed in 2020.
Upstream traffic increased due the use of videoconferences, remote
schooling, and similar applications. The National Cable &
Telecommunications Association (NCTA) and Comcast reported that while
downstream traffic grew 20%, upstream traffic grew by as much as
30-37% [NCTA2020] [Comcast2020]. Vodafone reported that upstream
traffic grew by 100% in some markets [Vodafone2020].
Ericsson's ConsumerLab surveyed users regarding their usage and
experiences during the crisis. Some of the key findings in
[ConsumerlabReport2020] were as follows:
* 9 in 10 users increased Internet activities, and time spent
connected increased. In addition, 1 in 5 started new online
activities; many in the older generation felt that they were
helped by video calling; parents felt that their children's
education was helped; and so on.
* Network performance was, in general, found satisfactory. 6 in 10
were very satisfied with fixed broadband, and 3 in 4 felt that
mobile broadband was the same or better compared to before the
crisis. Consumers valued resilience and quality of service as the
most important responsibility for network operators.
* Smartphone application usage changed, with the fastest growth in
apps related to COVID-19 tracking and information, remote working,
e-learning, wellness, education, remote health consultation, and
social shared experience applications. The biggest decreases were
in travel and booking, ride hailing, location, and parking
applications.
Some of the behaviors are likely permanent changes
[ConsumerlabReport2020]. The adoption of video calls and other new
services by many consumers, such as the older generation, is likely
going to have a long-lasting effect. Surveys in various
organizations point to a likely long-term increase in the number of
people interested in remote work [WorkplaceAnalytics2020]
[McKinsey2020].
3.2. Operational Practices and Architectural Considerations
The second and third days of the workshop focused on open discussions
of arising operational and architectural issues and the conclusions
that could be reached from previous discussions and other issues
raised in the position papers.
3.2.1. Digital Divide
Measurements from Fastly confirmed that Internet traffic volume in
multiple countries rose rapidly while COVID cases were increasing and
lockdown policies were coming into effect. Download speeds also
decreased but in a much less dramatic fashion than when overall
bandwidth usage increased. School closures led to a dramatic
increase in traffic volume in many regions, and other public policy
announcements triggered large traffic shifts. This suggests that
governments should coordinate with operators to allow time for
preemptive operational changes in some cases.
Measurements from the US showed that download rates correlate with
income levels. However, download rates in the lowest income zip
codes increased as the pandemic progressed, closing the divide with
higher income areas. One possible reason for this in the data is
decisions by some ISPs, such as Comcast and Cox, that increased
speeds for users on certain lower-cost plans and in certain areas.
This suggests that network capacity was available and that the
correlation between income and download rates was not necessarily due
to differences in the deployed infrastructure in different regions,
although it was noted that certain access link technologies provide
more flexibility than others in this regard.
3.2.2. Applications
Web conferencing systems (e.g., Microsoft Teams, Zoom, Webex) saw
incredible growth, with overnight traffic increases of 15-20% in
response to public policy changes, such as lockdowns. This required
significant and rapid changes in infrastructure provisioning.
Major video providers (YouTube, etc.) reduced bandwidth by 25% in
some regions. It was suggested that this had a huge impact on the
quality of videoconferencing systems until networks could scale to
handle the full bit rate, but other operators of some other services
saw limited impact.
Updates to popular games have a significant impact on network load.
Some discussions were reported between ISPs, CDNs, and the gaming
industry on possibly coordinating various high-bandwidth update
events, similar to what was done for entertainment/video download
speeds. There was an apparently difficult interplay between bulk
download and interactive real-time applications, potentially due to
buffer bloat and queuing delays.
It was noted that operators have experience with rapid growth of
Internet traffic. New applications with exponential growth are not
that unusual in the network, and the traffic spike due to the
lockdown was not that unprecedented for many. Many operators have
tools and mechanisms to deal with this. Ensuring that knowledge is
shared is a challenge.
Following these observations, traffic prioritization was discussed,
starting from Differentiated Services Code Point (DSCP) marking. The
question arose as to whether a minimal priority-marking scheme would
have helped during the pandemic, e.g., by allowing marking of less-
than-best-effort traffic. That discussion quickly devolved into a
more general QoS and observability discussion and, as such, also
touched on the effects of increased encryption. The group was not,
unsurprisingly, able to resolve the different perspectives and
interests involved, but the discussion demonstrated that progress was
made.
3.2.3. Observability
It is clear that there is a contrast in experience. Many operators
reported few problems in terms of metrics, such as measured download
bandwidth, while videoconferencing applications experienced
significant usability problems running on those networks. The
interaction between application providers and network providers
worked very smoothly to resolve these issues, supported by strong
personal contacts and relationships. But it seems clear that the
metrics used by many operators to understand their network
performance don't fully capture the impact on certain applications,
and there is an observability gap. Do we need more tools to figure
out the various impacts on user experience?
These types of applications use surprising amounts of Forward Error
Correction (FEC). Applications hide lots of loss to ensure a good
user experience. This makes it harder to observe problems. The
network can be behaving poorly, but the experience can be good
enough. Resiliency measures can improve the user experience but hide
severe problems. There may be a missing feedback loop between
application developers and operators.
It's clear that it's difficult for application providers and
operators to isolate problems. Is a problem due to the local Wi-Fi,
the access network, the cloud network, etc.? Metrics from access
points would help, but in general, lack of observability into the
network as a whole is a real concern when it comes to debugging
performance issues.
Further, it's clear that it can be difficult to route problem reports
to the person who can fix them, especially if the reported
information needs to be shared across multiple networks in the
Internet. COVID-enhanced cooperation made it easier to debug
problems; lines of communication are important.
3.2.4. Security
The increased threats and network security impacts arising from
COVID-19 fall into two areas: (1) the agility of malicious actors to
spin up new campaigns using COVID-19 as a lure, and (2) the increased
threat surface from a rapid shift towards working from home.
During 2020, there was a shift to home working generally, and in the
way in which people used the network. IT departments rolled out new
equipment quickly and used technologies like VPNs for the first time,
while others put existing solutions under much greater load. As VPN
technology became more widespread and more widely used, it arguably
became a more valuable target; one Advanced Persistent Threat group
(APT29) was successful in using recently published exploits in a
range of VPN software to gain initial footholds [Kirsty2020].
Of all scams detected by the United Kingdom National Cyber Security
Centre (UK NCSC) that purported to originate from the UK Government,
more related to COVID-19 than any other subject. There are other
reports of a strong rise in phishing, fraud, and scams related to
COVID [Kirsty2020]. Although the overall levels of cybercrime have
not increased from the data seen to date, there was certainly a shift
in activity as both the NCSC and the Department of Homeland Security
Cybersecurity and Infrastructure Security Agency (DHS CISA) saw
growing use of COVID-19-related themes by malicious cyber actors as a
lure. Attackers used COVID-19-related scams and phishing emails to
target individuals, small and medium businesses, large organizations,
and organizations involved in both national and international
COVID-19 responses (healthcare bodies, pharmaceutical companies,
academia, and medical research organizations). New targets (for
example, organizations involved in COVID-19 vaccine development) were
attacked using VPN exploits, highlighting the potential consequences
of vulnerable infrastructure.
It's unclear how to effectively detect and counter these attacks at
scale. Approaches such as using Indicators of Compromise and
crowdsourced flagging of suspicious emails were found to be effective
in response to COVID-19-related scams [Kirsty2020], and observing the
DNS to detect malicious use is widespread and effective. The use of
DNS over HTTPS offers privacy benefits, but current deployment models
can bypass these existing protective DNS measures.
It was also noted that when everyone moves to performing their job
online, lack of understanding of security becomes a bigger issue. Is
it reasonable to expect every user of the Internet to have password
training? Or is there a fundamental problem with a technical
solution? Modern advice advocates a layered approach to security
defenses, with user education forming just one of those layers.
Communication platforms such as Zoom are not new: many people have
used them for years, but as COVID-19 saw an increasing number of
organizations and individuals turning to these technologies, they
became an attractive target due to increased usage. In turn, there
was an increase in malicious cyber actor activity, either through
hijacking online meetings that were not secured with passwords or
leveraging unpatched software as an attack vector. How can new or
existing measures protect users from the attacks levied against the
next vulnerable service?
Overall, it may be that there were fewer security challenges than
expected arising from many people suddenly working from home.
However, the agility of attackers, the importance of robust and
scalable defense mechanisms, and some existing security problems and
challenges may have become even more obvious and acute with an
increased use of Internet-based services, particularly in a pandemic
situation and in times of uncertainty, where users can be more
vulnerable to social engineering techniques and attacks.
3.2.5. Discussion
There is a concern that we're missing observability for the network
as a whole. Each application provider and operator has their own
little lens. No one has the big-picture view of the network.
How much of a safety margin do we need? Some of the resiliency comes
from us not running the network too close to its limit. This allows
traffic to shift and gives headroom for the network to cope. The
best-effort nature of the network may help here. Using techniques to
run the network closer to its limits usually improves performance,
but highly optimized networks may be less robust.
Finally, it was observed that we get what we measure. There may be
an argument for operators to perhaps shift their measurement focus
away from pure capacity to instead measure Quality of Experience
(QoE) or resilience. The Internet is a critical infrastructure, and
people are realizing that now. We should use this as a wake-up call
to improve resilience, both in protocol design and operational
practice, not necessarily to optimize for absolute performance or
quality of experience.
3.3. Conclusions
There is a wealth of data about the performance of the Internet
during the COVID-19 crisis. The main conclusion from the various
measurements is that fairly large shifts occurred. And those shifts
were not merely about exchanging one application for another; they
actually impacted traffic flows and directions and caused, in many
cases, a significant traffic increase. Early reports also seem to
indicate that the shifts have gone relatively smoothly from the point
of view of overall consumer experience.
An important but not so visible factor that led to running smoothly
was that many people and organizations were highly motivated to
ensure good user experience. A lot of collaboration happened in the
background, problems were corrected, many providers significantly
increased their capacity, and so on.
On the security front, the COVID-19 crisis showcased the agility with
which malicious actors can move in response to a shift in user
Internet usage and the vast potential of the disruption and damage
that they can inflict. Equally, it showed the agility of defenders
when they have access to the tools and information they need to
protect users and networks, and it showcased the power of Indicators
of Compromise when defenders around the world are working together
against the same problem.
In general, the Internet also seems well suited for adapting to new
situations, at least within some bounds. The Internet is designed
for flexibility and extensibility, rather than being optimized for
today's particular traffic types. This makes it possible to use it
for many applications and in many deployment situations and to make
changes as needed. The generality is present in many parts of the
overall system, from basic Internet technology to browsers and from
name servers to content delivery networks and cloud platforms. When
usage changes, what is needed is often merely different services,
perhaps some reallocation of resources as well as consequent
application and continuation of existing security defenses, but not
fundamental technology or hardware changes.
On the other hand, this is not to say that no improvements are
needed:
* We need a better understanding of the health of the Internet.
Going forward, the critical nature that the Internet plays in our
lives means that the health of the Internet needs to receive
significant attention. Understanding how well networks work is
not just a technical matter; it is also of crucial importance to
the people and economies of the societies using it. Projects and
research that monitor Internet and services performance on a broad
scale and across different networks are therefore important.
* We need to maintain defensive mechanisms to be used in times of
crisis. Malicious cyber actors are continually adjusting their
tactics to take advantage of new situations, and the COVID-19
pandemic is no exception. Malicious actors used the strong
appetite for COVID-19-related information as an opportunity to
deliver malware and ransomware and to steal user credentials.
Against the landscape of a shift to working from home and an
increase in users vulnerable to attack, and as IT departments were
often overwhelmed by rolling out new infrastructure and devices,
sharing Indicators of Compromise (IoC) was a vital part of the
response to COVID-19-related scams and attacks.
* We need to ensure that broadband is available to all and that
Internet services equally serve different groups. The pandemic
has shown how the effects of the digital divide can be amplified
during a crisis and has further highlighted the importance of
equitable Internet access.
* We need to continue to work on all the other improvements that are
seen as necessary anyway, such as further improvements in
security, the ability for networks and applications to collaborate
better, etc.
* We need to ensure that informal collaboration between different
parties involved in the operation of the network continues and is
strengthened to ensure continued operational resilience.
4. Feedback on Meeting Format
While there are frequently virtual participants in IAB workshops, the
IAB had no experience running workshops entirely virtually.
Feedback on this event format was largely positive, however. It was
particularly useful that as the three sessions were scheduled on
Monday, Wednesday, and Friday, the time in between the sessions could
be used for mailing list discussion and compilation of additional
workshop material. The positive feedback was likely at least partly
due to the fact that many of the workshop participants knew one
another from previous face-to-face events (primarily IETF meetings).
The process for sending invitations to the workshop should be
improved for next time, however, as a few invitations were initially
lost. In a virtual meeting, it may be more reasonable to invite not
just one person but all coauthors of a paper, for instance. At least
for this workshop, we did not appear to suffer from having too many
participants, and in many cases, there may be some days when a
particular participant may not be able to attend a session.
5. Position Papers
The following position papers were received, in alphabetical order:
* Afanasyev, A., Wang, L., Yeh, E., Zhang, B., and Zhang, L.:
Identifying the Disease from the Symptoms: Lessons for Networking
in the COVID-19 Era [Afxanasyev2020]
* Arkko, J.: Observations on Network User Behaviour During COVID-19
[Arkko2020]
* Bronzino, F., Culley, E., Feamster, N., Liu, S., Livingood, J.,
and Schmitt, P.: IAB COVID-19 Workshop: Interconnection Changes in
the United States [Bronzino2020]
* Campling, A. and Lazanski, D.: Will the Internet Still Be
Resilient During the Next Black Swan Event? [Campling2020]
* Cho, K.: On the COVID-19 Impact to broadband traffic in Japan
[Cho2020]
* Clark, D.: Measurement of congestion on ISP interconnection links
[Clark2020]
* Favale, T., Soro, F., Trevisan, M., Drago, I., and Mellia, M.:
Campus traffic and e-Learning during COVID-19 pandemic
[Favale2020]
* Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese, I.,
Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador, J., Vallina-
Rodriguez, N., Hohlfeld, O., and Smaragdakis, G.: A view of
Internet Traffic Shifts at ISP and IXPs during the COVID-19
Pandemic [Feldmann2020]
* Fontugne, R., Shah, A., and Cho, K.: The Impact of COVID-19 on
Last-mile Latency [Fontugne2020]
* Gillmor, D.: Vaccines, Privacy, Software Updates, and Trust
[Gillmor2020]
* Gu, Y. and Li, Z.: Covid 19 Impact on China ISP's Network Traffic
Pattern and Solution Discussion [Gu2020]
* Jennings, C. and Kozanian, P.: WebEx Scaling During Covid
[Jennings2020]
* Lutu, A., Perino, D., Bagnulo, M., Frias-Martinez, E., and
Khangosstar, J.: A Characterization of the COVID-19 Pandemic
Impact on a Mobile Network Operator Traffic [Lutu2020]
* Mok, R., and claffy, kc: Measuring the impact of COVID-19 on cloud
network performance [Mok2020]
* Paine, K.: IAB COVID-19 Network Impacts [Kirsty2020]
6. Program Committee
The workshop program committee members were Jari Arkko, Stephen
Farrell, Cullen Jennings, Colin Perkins, Ben Campbell, and Mirja
Kühlewind.
7. Informative References
[Afxanasyev2020]
Afanasyev, A., Wang, L., Yeh, E., Zhang, B., and L. Zhang,
"Identifying the Disease from the Symptoms: Lessons for
Networking in the COVID-19 Era", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/12/IAB-
COVID-19-WS_102820.pdf>.
[Arkko2020]
Arkko, J., "Observations on Network User Behaviour During
COVID-19", October 2020, <https://www.iab.org/wp-content/
IAB-uploads/2020/10/covid19-arkko.pdf>.
[Bronzino2020]
Bronzino, F., Culley, E., Feamster, N., Liu, S.,
Livingood, J., and P. Schmitt, "IAB COVID-19 Workshop:
Interconnection Changes in the United States", Work in
Progress, Internet-Draft, draft-feamster-livingood-iab-
covid19-workshop-01, 28 October 2020,
<https://datatracker.ietf.org/doc/html/draft-feamster-
livingood-iab-covid19-workshop-01>.
[Campling2020]
Campling, A. and D. Lazanski, "Will the Internet Still Be
Resilient During the Next Black Swan Event?", October
2020, <https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-campling.pdf>.
[Cho2020] Cho, K., "On the COVID-19 Impact to broadband traffic in
Japan", October 2020, <https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-cho.pdf>.
[Clark2020]
Clark, D., "Measurement of congestion on ISP
interconnection links", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-clark.pdf>.
[Comcast2020]
Comcast, "COVID-19 Network Update", May 2020,
<https://corporate.comcast.com/covid-19/network/may-
20-2020>.
[ConsumerlabReport2020]
Ericsson ConsumerLab, "Connectivity in a COVID-19 world:
Keeping consumers connected in a global crisis",
<https://www.ericsson.com/en/reports-and-
papers/consumerlab/reports/keeping-consumers-connected-
during-the-covid-19-crisis>.
[Favale2020]
Favale, T., Soro, F., Trevisan, M., Drago, I., and M.
Mellia, "Campus traffic and e-Learning during COVID-19
pandemic", DOI 10.1016/j.comnet.2020.107290, October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-favale.pdf>.
[Feldmann2020]
Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese,
I., Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador,
J., Vallina-Rodriguez, N., Hohlfeld, O., and G.
Smaragdakis, "A view of Internet Traffic Shifts at ISP and
IXPs during the COVID-19 Pandemic", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-feldmann.pdf>.
[Fontugne2020]
Fontugne, R., Shah, A., and K. Cho, "The Impact of
COVID-19 on Last-mile Latency", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-fontugne.pdf>.
[Fontugne2020-1]
Fontugne, R., Shah, A., and K. Cho, "Persistent Last-mile
Congestion: Not so Uncommon", Proceedings of the ACM
Internet Measurement Conference (IMC '20),
DOI 10.1145/3419394.3423648, October 2020,
<https://doi.org/10.1145/3419394.3423648>.
[Gillmor2020]
Gillmor, D., "Vaccines, Privacy, Software Updates, and
Trust", October 2020, <https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-gillmor.pdf>.
[Gu2020] Gu, Y. and Z. Li, "Covid 19 Impact on China ISP's Network
Traffic Pattern and Solution Discussion", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-gu.pdf>.
[Jennings2020]
Jennings, C. and P. Kozanian, "WebEx Scaling During
Covid", October 2020, <https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-jennings.pdf>.
[Kirsty2020]
Paine, K., "IAB COVID-19 Network Impacts", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-kirstyp.pdf>.
[Lutu2020] Lutu, A., Perino, D., Bagnulo, M., Frias-Martinez, E., and
J. Khangosstar, "A Characterization of the COVID-19
Pandemic Impact on a Mobile Network Operator Traffic",
DOI 10.1145/3419394.3423655, October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-lutu.pdf>.
[McKinsey2020]
Boland, B., De Smet, A., Palter, R., and A. Sanghvi,
"Reimagining the office and work life after COVID-19",
June 2020, <https://www.mckinsey.com/~/media/McKinsey/Busi
ness%20Functions/Organization/Our%20Insights/Reimagining%2
0the%20office%20and%20work%20life%20after%20COVID%2019/
Reimagining-the-office-and-work-life-after-COVID-
19-final.pdf>.
[Mok2020] Mok, R. and kc. claffy, "Measuring the impact of COVID-19
on cloud network performance", October 2020,
<https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-mok.pdf>.
[NCTA2020] NCTA, "COVID-19: How Cable's Internet Networks Are
Performing: Metrics, Trends & Observations",
<https://www.ncta.com/COVIDdashboard>.
[Vodafone2020]
Vodafone, "An update on Vodafone's networks", April 2020,
<https://www.vodafone.com/covid19/news/update-on-vodafone-
networks>.
[WorkplaceAnalytics2020]
Lister, K., "Work-at-Home After Covid-19--Our Forecast",
March 2020, <https://globalworkplaceanalytics.com/work-at-
home-after-covid-19-our-forecast>.
Appendix A. Workshop Participants
The following is an alphabetical list of participants in the
workshop.
* Jari Arkko (Ericsson/IAB)
* Ben Campbell (Independent/IAB)
* Andrew Campling (419 Consulting)
* Kenjiro Cho (IIJ)
* kc claffy (CAIDA)
* David Clark (MIT CSAIL)
* Chris Dietzel (DE-CIX)
* Idilio Drago (University of Turin)
* Stephen Farrell (Trinity College Dublin/IAB)
* Nick Feamster (University of Chicago)
* Anja Feldmann (Max Planck Institute for Informatics)
* Romain Fontugne (IIJ Research Lab)
* Oliver Gasser (Max Planck Institute for Informatics)
* Daniel Kahn Gillmor (ACLU)
* Yunan Gu (Huawei)
* Oliver Hohlfeld (Brandenburg University of Technology (BTU))
* Jana Iyengar (Fastly)
* Cullen Jennings (Cisco/IAB)
* Mirja Kühlewind (Ericsson/IAB)
* Dominique Lazanski
* Zhenbin Li (Huawei/IAB)
* Franziska Lichtblau (Max Planck Institute for Informatics)
* Jason Livingood (Comcast)
* Andra Lutu (Telefonica Research)
* Vesna Manojlovic (RIPE NCC)
* Rüdiger Martin (EC)
* Larry Masinter (Retired)
* Matt Matthis (Google)
* Jared Mauch (Akamai/IAB)
* Deep Medhi (NSF)
* Marco Mellia (Politecnico di Torino)
* Ricky Mok (CAIDA)
* Karen O'Donoghue (Internet Society)
* Kirsty Paine (NCSC)
* Diego Perino (Telefonica Research)
* Colin Perkins (University of Glasgow/IRTF/IAB)
* Enric Pujol (Benocs)
* Anant Shah (Verizon Media Platform)
* Francesca Soro (Politecnico di Torino)
* Brian Trammell (Google)
* Martino Trevisan
* Georgios Tselentis (European Commission)
* Lan Wang (University of Memphis)
* Rob Wilton (Cisco)
* Jiankang Yao (CNNIC)
* Lixia Zhang (UCLA)
IAB Members at the Time of Approval
Internet Architecture Board members at the time this document was
approved for publication were:
Jari Arkko
Deborah Brungard
Ben Campbell
Lars Eggert
Wes Hardaker
Cullen Jennings
Mirja Kühlewind
Zhenbin Li
Jared Mauch
Tommy Pauly
David Schinazi
Russ White
Jiankang Yao
Acknowledgments
The authors would like to thank the workshop participants, the
members of the IAB, the program committee, the participants in the
architecture discussion list for the interesting discussions, and
Cindy Morgan for the practical arrangements.
Further special thanks to those participants who also contributed to
this report: Romain Fontugne provided text based on his blog post at
<https://eng-blog.iij.ad.jp/archives/7722>; Ricky Mok for text on
cloud platforms; Martino Trevisan for text on campus networks; David
Clark on congestion measurements at interconnects; Oliver Hohlfeld
for the text on traffic growth, changes in traffic shifts, campus
networks, and interconnections; Andra Lutu on mobile networks; and
Kirsty Paine for text on security impacts. Thanks to Jason Livingood
for his review and additions.
Authors' Addresses
Jari Arkko
Ericsson
Email: jari.arkko@ericsson.com
Stephen Farrell
Trinity College Dublin
Email: stephen.farrell@cs.tcd.ie
Mirja Kühlewind
Ericsson
Email: mirja.kuehlewind@ericsson.com
Colin Perkins
University of Glasgow
Email: csp@csperkins.org