Internet DRAFT - draft-iab-covid19-workshop
draft-iab-covid19-workshop
Network Working Group J. Arkko
Internet-Draft Ericsson
Intended status: Informational S. Farrell
Expires: 6 November 2021 Trinity College Dublin
M. Kühlewind
Ericsson
C. Perkins
University of Glasgow
5 May 2021
Report from the IAB COVID-19 Network Impacts Workshop 2020
draft-iab-covid19-workshop-03
Abstract
The COVID-19 pandemic caused changes in Internet user behavior,
particularly during the introduction of the 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 on-going travel
and contact restrictions at that time.
Discussion Venues
This note is to be removed before publishing as an RFC.
Source for this draft and an issue tracker can be found at
https://github.com/intarchboard/covid19-workshop.
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-
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Workshop Topics and Discussion . . . . . . . . . . . . . . . 5
3.1. Measurement-based Observations on Network Traffic
Dynamics . . . . . . . . . . . . . . . . . . . . . . . . 5
3.1.1. Overall Traffic Growth . . . . . . . . . . . . . . . 6
3.1.2. Changes in Application Use . . . . . . . . . . . . . 6
3.1.3. Mobile Networks and Mobility . . . . . . . . . . . . 8
3.1.4. A Deeper Look at Interconnections . . . . . . . . . . 9
3.1.5. Cloud Platforms . . . . . . . . . . . . . . . . . . . 9
3.1.6. Last-Mile Congestion . . . . . . . . . . . . . . . . 10
3.1.7. User Behaviour . . . . . . . . . . . . . . . . . . . 10
3.2. Operational Practices and Architectural Considerations . 11
3.2.1. Digital Divide . . . . . . . . . . . . . . . . . . . 11
3.2.2. Applications . . . . . . . . . . . . . . . . . . . . 12
3.2.3. Observability . . . . . . . . . . . . . . . . . . . . 13
3.2.4. Security . . . . . . . . . . . . . . . . . . . . . . 13
3.2.5. Discussion . . . . . . . . . . . . . . . . . . . . . 15
3.3. Conclusions . . . . . . . . . . . . . . . . . . . . . . . 15
4. Feedback on Meeting Format . . . . . . . . . . . . . . . . . 17
5. Position Papers . . . . . . . . . . . . . . . . . . . . . . . 17
6. Workshop participants . . . . . . . . . . . . . . . . . . . . 19
7. Program Committee . . . . . . . . . . . . . . . . . . . . . . 21
8. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 21
9. Informative References . . . . . . . . . . . . . . . . . . . 21
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Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 24
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 on-
going travel and contact restrictions at that time.
COVID-19 has caused changes in user behavior, which in turn drove
change to Internet traffic. These changes in user behavior appeared
rather abruptly and were significant, in particular during the
introduction of the initial quarantine and work-from-home
arrangements. This caused changes to Internet traffic in terms of
volumes, location, as well as shifts in the type of applications
used. This shift in traffic as well as user behavior created also a
shift in security partices as well as attack patterns that made use
of the attack surface resulting from the shift to home-working in a
global crisis.
Announcement for the workshop was sent out in July 2020, requesting
interested parties to submit position papers for the workshop program
committee. A total of 15 position papers were received from
altogether 33 authors. 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 45 participants, listed in Section 6.
The workshop was held over one week hosting three sessions covering
i) measurements and observations, ii) operational and security
issues, and iii) future consideration and conclusions. As these
three sessions were scheduled Monday, Wednesday, and Friday a
positive side effect was that the time in between could be used for
mailing list discussion and compilation of additional workshop
material.
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2. Scope
The COVID-19 pandemic has had a tremendous impact on people's lives
and the 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 a 20% traffic growth or more 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 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 has 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 by its own right. How that impacted 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 compute 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, or
to prepare for future situations -- crises or otherwise - that impact
networking. Or even 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 about traffic changes, user experience and problems,
service performance, and other relevant aspects
* discussion about the behind the scenes network management and
expansion activities
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* experiences in the fields of general Internet connectivity,
conferencing, media/entertainment, and Internet infrastructure
* lessons learned for preparedness and operations
* lessons learned for 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 get a better understanding of
the situation, covering different angles and aspects of network
traffic and kind of networks.
Changes in Internet traffic due to the COVID-19 pandemic affected
different networks in various ways. Yet all networks observed some
form of change, be it a reduction in traffic, an increase in traffic,
a change in working days and weekend days patterns, or a change in
traffic classes. Traffic volume, directionality ratios, and its
source and destination are radically different than from before
COVID-19.
At a high level, while traffic from home networks increased
significantly, the traffic in mobile networks decreased as a result
of reduced population mobility. The observed behavior in mobile
networks is antagonistic, yet complementary, to the one observed in
residential ISPs. In residential networks there was a strong
increase in video conferencing and remote learning application
traffic due to the shift for working and learning at home. With that
shift, the typical diurnal usage patterns in network traffic also
changed, with peak times occuring earlier in the day and lasting
longer over the day - reflecting the start of the work or school day
from home. This behavior is antagonistic, yet complementary, to the
one observed in residential ISPs.
While diurnal congestion at interconnect point as well in certain
last mile network was reported, mainly in March, no persitent
congestion was observed. Further, a downward trends in download
throughput to certain cloud regions was measured, which can probably
explained with the increase use of cloud services. This gives
another indication that the scalng of shared resources in the
Internet is working reasonably well enough to handle even larger
changes in traffic as experience during the first nearly global
lockdown of the COVID-19 pandemic.
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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 traffic growth rate in March and
April. That is, after the lockdown was implemented in March, a
traffic increase of 15-20% at the ISP as well as the three IXPs was
observed. That represents the traffic growth expected in a typical
year which now took place in the matter of a few weeks only---a
substantial increase. At DE-CIX Frankfurt, the world's largest
Internet Exchange Point in terms of data throughput, the year 2020
has seen 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 video conferencing and other remote
work and school applications.
Most traffic increases happened during non-traditional 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 perform some of their daily habits outside of
their home again, as expected, there was a decrease of 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 network it was
observed [Feldmann2020] that traffic associated with web
conferencing, video, and gaming increased largely in March 2020 as a
result of the increasing user demand for solutions like Zoom or
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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---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
ones.
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 University (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 however not lead to
noticeable performance impairments, nor have significantly poor
performance been observed for 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, which 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 also
potentially caused by overseas students (mainly from Latin America
and East Asia as suggested by the AS numbers from which these
connections came from) who accessed university network resources from
their home countries.
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Given the fact that the users of the academic network (e.g., students
and research staff) had to leave the campus as a response to lockdown
measures, also the traffic in and out (i.e., ingress and egress)
ratio changed drastically. Prior to the lockdown, the incoming
traffic was much larger then the outgoing traffic. This changed to a
more balanced ratio. This change of traffic asymmetry can be
explained by the nature of remote work. On the one end, users
connected to the network services mainly to access resources, hence
the increase in outgoing traffic. On the other end, 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 signalling 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
the residents temporarily relocated during the lockdown.
These mobility changes had immediate implications in traffic patterns
of the cellular network. The downlink data traffic volume aggregated
for all bearers (including conversational voice) decreased for all UK
by up to 25% during the lockdown period. This correlates with the
reduction in mobility that was observed country-wide, which likely
resulted in people relying more on broadband residential 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, further corroborates the drop in cellular connectivity usage.
The total uplink data traffic volume, on the other hand, experienced
little changes (between -7% and +1,5%) during lockdown. This was
mainly due to the increase of 4G voice traffic (i.e., VoLTE) across
the UK that peaked at 150% after the lockdown compared to the
national medial value before the pandemic, thus compensating for the
decrease in data traffic in the uplink.
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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 volumes, radio load
and active users) was observed than in rural areas. In the case of
London, this was likely due to geodemographics of the central
districts, which include many seasonal residents (e.g., tourists),
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 increases varied, with some
networks that hosted popular applications such as video conferencing
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 a higher traffic
demand from residential users.
Measurements of interconnection links at major US ISPs by CAIDA and
MIT found some evidence of diurnal congestion around the March 2020
timeframe [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 video conferencing and remote learning tools to practise
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 perform 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:
* 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 U.S.
Their users could have suffered from poor video streaming or file
download performance from the cloud.
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* 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 IMC'20 research paper Fontugne et al.
investigated last-mile latency using traceroute data from RIPE Atlas
probes located in 646 ASes and looked for recurrent performance
degradation [Fontugne2020-1]. They found that in normal times Atlas
probes in only 10% ASes experience persistent last-mile congestion,
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
certain parts of the world. They found Japan to be the most impacted
country in their study looking specifically at NTT OCN, but noting
similar observations for several Japanese networks, including IIJ
(AS2497).
From mid-2020 onwards, they however 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 Behaviour
The type of traffic needed by the users also changed in 2020.
Upstream traffic increased due the use of video conferences, remote
schooling, and similar applications. The NCTA and Comcast reported
that while downstream traffic grew 20%, upstream traffic grew as much
as 30% to 37% [NCTA2020] [Comcast2020]. Vodafone reported that
upstream traffic grew 100% in some markets [Vodafone2020].
Ericsson's Consumer Lab surveyed users for their usage and
experiences during the crisis. Some of the key findings in
[ConsumerlabReport2020] were:
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* 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 task for network operators.
* Smartphone application usage changed, with 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. Biggest decreases were in
travel and booking, ride hailing, location, and parking
applications.
Some of the behaviours 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 day of the workshop were held based on more open
discussions focussed on operational issues and the architectural
issues arising or other conclusions that could be reached.
3.2.1. Digital Divide
Measurements from Fastly confirmed that Internet traffic volume, in
multiple countries, rose rapidly at the same time as COVID cases
increased and lockdown policies came into effect. Download speeds
also decreased, but in a much less dramatic fashion than 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 might usefully coordinate with operators to allow time
for pre-emptive 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
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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 lower-cost certain 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
The 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
quality of videoconferencing systems until networks could scale to
handle full bit-rate, but other operators of some other services saw
limited impact.
Updates to popular games has 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 of 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 if
shared is a challenge.
Following these observations traffic prioritisation was discussed,
starting from DSCP marking, basically wondering if 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 touching on the effects of increased
encryption. The group was not, unsurprisingly, able to resolve the
different perspectives and interests involved in that, but the
discussion demonstrated that progress is made (and being less
heated).
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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 video conferencing 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 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 WiFi,
the access network, 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, 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 home working.
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During 2020, there was a shift to home working generally, and in the
way in which people use the network, with IT departments rolling out
new equipment quickly and using technologies like VPNs for the first
time, while others put existing solutions under much greater load.
As VPN technology became more widespread and more used, it arguably
became a more valuable target; one Advanced (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 UK NCSC (United Kingdom National Cyber
Security Centre) that purported to originate from 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, from the data seen to date, the overall
levels of cyber crime have not increased, there was certainly a shift
in activity - as both the NCSC and CISA (DHS Cybersecurity and
Infrastructure Security Agency) saw a 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 organisations, and organisations involved in
both national and international COVID-19 responses (healthcare
bodies, pharmaceutical companies, academia and medical research
organisations). New targets, for example organisations 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 crowd-
sourced flagging of suspicious emails were found to be effective in
the response to COVID-19-related scams[Kirsty2020], and observing 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 take password
training? Or is there a fundamental problem with a technical
solution? Modern advice advocates a layered approach to security
defences, with user education forming just one of those layers.
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Communication platforms such as Zoom are not new: many people have
used them for years, but as COVID-19 saw an increasing number of
organisations 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 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 defence 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 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. Techniques to run
the network closer to its limits improve performance in the usual
case, but highly optimised networks may be less robust.
Finally, it was observed that we get what we measure. There may be
an argument for operators to shift their measurement focus perhaps
away from pure capacity, to rather measure QoE or resilience. The
Internet is a critical infrastructure, and people are realising that
now. We should use this as a wake-up-call to improve resilience,
both in protocol design and operational practice, not necessarily to
optimise for absolute performance or quality of experience.
3.3. Conclusions
There is a wealth of data about the performance of the Internet
during the crisis. The main conclusion from the various measurements
is that fairly large shifts occurred. And those shifts were not
merely about changing 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
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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 this was that many
people and organizations where highly motivated to ensure good
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 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 optimized for today's
particular traffic. This makes it possible to use it for many
applications, in many deployment situations, and make changes as
needed. The generality is present in many parts of the overall
system, from basic Internet technology to browsers, from name servers
to content delivery networks and cloud platforms. When usage
changes, what is needed is often merely different services, perhaps
some re-allocation of resources, as well as consequent application
and continuation of existing security defences, 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 economy of the societies using it. Projects and
research that monitor Internet and services performance in 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 high appetite
for COVID-19 related information as an opportunity to deliver
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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, IoC
sharing 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, 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 Monday,
Wednesday, and Friday, the time in between 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, and in a virtual meeting it may be more reasonable to invite
not just one person but all co-authors of a paper, for instance. At
least for this workshop, we did not appear to suffer from 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:
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* Afxanasyev, 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, Jari: 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, Andrew and Lazanski, Dominique: Will the Internet Still
Be Resilient During the Next Black Swan Event? [Campling2020]
* Cho, Kenjiro: 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, Ricky, and claffy, kc: Measuring the impact of COVID-19 on
cloud network performance [Mok2020]
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* Kirsty P: IAB COVID-19 Network Impacts [Kirsty2020]
6. 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 Kuhlewind (Ericsson/IAB)
* Franziska Lichtblau (Max Planck Institute for Informatics)
* Dominique Lazanski
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* Zhenbin Li (Huawei/IAB)
* Jason Livingood (Comcast)
* Andra Lutu (Telefonica Research)
* Vesna Manojlovic (RIPE NCC)
* R Martin EC (?)
* Matt Matthis (Google)
* Larry Masinter (Retired)
* Jared Mauch (Akamai/IAB)
* Deep Medhi (NSF)
* Marco Mellia (Politecnico di Torino)
* Ricky Mok (CAIDA)
* Karen O'Donoghue (Internet Society)
* Kirsty P (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)
* Gergios Tselentis (European Commission)
* Martino Trevisan
* Lan Wang (University of Memphis)
* Rob Wilton (Cisco)
* Jiankang Yao (CNNIC)
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* Lixia Zhang (UCLA)
7. Program Committee
The workshop Program Committee members were Jari Arkko, Stephen
Farrell, Cullen Jennings, Colin Perkins, Ben Campbell, and Mirja
Kuehlewind.
8. 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 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
platform; 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; Kirsty Paine for
text on security impacts; and thanks to Jason Livingood for his
review and additions.
9. Informative References
[Afxanasyev2020]
Afxanasyev, A., Wang, L., Yeh, E., Zhang, B., and L.
Zhang, "Identifying the Disease from the Symptoms: Lessons
for Networking in the COVID-19 Era", https://www.iab.org/
wp-content/IAB-uploads/2020/12/IAB-COVID-
19-WS_102820.pdf , October 2020.
[Arkko2020]
Arkko, J., "Observations on Network User Behaviour During
COVID-19", https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-arkko.pdf , October 2020.
[Bronzino2020]
Bronzino, F., Culley, E., Feamster, N., Liu, S.,
Livingood, J., and P. Schmitt, "IAB COVID-19 Workshop:
Interconnection Changes in the United States",
https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-feamster.pdf , October 2020.
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[Campling2020]
Campling, A. and D. Lazanski, "Will the Internet Still Be
Resilient During the Next Black Swan Event?",
https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-campling.pdf , October 2020.
[Cho2020] Cho, K., "On the COVID-19 Impact to broadband traffic in
Japan", https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-cho.pdf , October 2020.
[Clark2020]
Clark, D., "Measurement of congestion on ISP
interconnection links", https://www.iab.org/wp-content/
IAB-uploads/2020/10/covid19-clark.pdf , October 2020.
[Comcast2020]
Comcast, ., "COVID-19 Network Update",
https://corporate.comcast.com/covid-19/network/may-20-2020
, May 2020.
[ConsumerlabReport2020]
Ericsson Consumer & IndustryLab, ., "Keeping consumers
connected in a COVID-19 context",
https://www.ericsson.com/en/reports-and-
papers/consumerlab/reports/keeping-consumers-connected-
during-the-covid-19-crisis , June 2020.
[Favale2020]
Favale, T., Soro, F., Trevisan, M., Drago, I., and M.
Mellia, "Campus traffic and e-Learning during COVID-19
pandemic", https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-favale.pdf , October 2020.
[Feldmann2020]
Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese,
I., Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador,
J., N Vallina-Rodriguez, ., Hohlfeld, O., and G.
Smaragdakis, "A view of Internet Traffic Shifts at ISP and
IXPs during the COVID-19 Pandemic", https://www.iab.org/
wp-content/IAB-uploads/2020/10/covid19-feldmann.pdf ,
October 2020.
[Fontugne2020]
Fontugne, R., Shah, A., and K. Cho, "The Impact of
COVID-19 on Last-mile Latency", https://www.iab.org/wp-
content/IAB-uploads/2020/10/covid19-fontugne.pdf , October
2020.
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[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) , October 2020.
[Gillmor2020]
Gillmor, D., "Vaccines, Privacy, Software Updates, and
Trust", https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-gillmor.pdf , October 2020.
[Gu2020] Gu, Y. and Z. Li, "Covid 19 Impact on China ISP's Network
Traffic Pattern and Solution Discussion",
https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-gu.pdf , October 2020.
[Jennings2020]
Jennings, C. and P. Kozanian, "WebEx Scaling During
Covid", https://www.iab.org/wp-content/IAB-
uploads/2020/10/covid19-jennings.pdf , October 2020.
[Kirsty2020]
Kirsty P, ., "IAB COVID-19 Network Impacts",
https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-kirstyp.pdf , October 2020.
[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",
https://www.iab.org/wp-content/IAB-uploads/2020/10/
covid19-lutu.pdf , October 2020.
[McKinsey2020]
Boland, B., De Smet, A., Palter, R., and A. Sanghvi,
"Reimagining the office and work life after COVID-19", htt
ps://www.mckinsey.com/~/media/McKinsey/Business%20Function
s/Organization/Our%20Insights/Reimagining%20the%20office%2
0and%20work%20life%20after%20COVID%2019/Reimagining-the-
office-and-work-life-after-COVID-19-final.pdf , June 2020.
[Mok2020] Mok, R. and . kc claffy, "Measuring the impact of COVID-19
on cloud network performance", https://www.iab.org/wp-
content/IAB-uploads/2020/10/covid19-mok.pdf , October
2020.
[NCTA2020] NCTA, ., "COVID-19: How Cable's Internet Networks Are
Performing: Metrics, Trends & Observations",
https://www.ncta.com/COVIDdashboard , 2020.
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[Vodafone2020]
Vodafone, ., "An update on Vodafone's networks",
https://www.vodafone.com/covid19/news/update-on-vodafone-
networks , April 2020.
[WorkplaceAnalytics2020]
Lister, K., "Work-At-Home After Covid-19—Our Forecast",
https://globalworkplaceanalytics.com/work-at-home-after-
covid-19-our-forecast , 2020.
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
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