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  <front>
    <title abbrev="IAB COVID-19 Network Impacts Workshop 2020">Report from the IAB COVID-19 Network Impacts Workshop 2020</title>
    <seriesInfo name="Internet-Draft" value="draft-iab-covid19-workshop-02"/>
    <author initials="J." surname="Arkko" fullname="Jari Arkko">
      <organization>Ericsson</organization>
      <address>
        <email>jari.arkko@ericsson.com</email>
      </address>
    </author>
    <author initials="S." surname="Farrell" fullname="Stephen Farrell">
      <organization>Trinity College Dublin</organization>
      <address>
        <email>stephen.farrell@cs.tcd.ie</email>
      </address>
    </author>
    <author initials="M." surname="Kühlewind" fullname="Mirja Kühlewind">
      <organization>Ericsson</organization>
      <address>
        <email>mirja.kuehlewind@ericsson.com</email>
      </address>
    </author>
    <author initials="C." surname="Perkins" fullname="Colin Perkins">
      <organization>University of Glasgow</organization>
      <address>
        <email>csp@csperkins.org</email>
      </address>
    </author>
    <date year="2021" month="May" day="05"/>
    <keyword>Internet-Draft</keyword>
    <abstract>
      <t>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.</t>
      <t>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.</t>
    </abstract>
    <note removeInRFC="true">
      <name>Discussion Venues</name>
      <t>Source for this draft and an issue tracker can be found at
  <eref target="https://github.com/intarchboard/covid19-workshop"/>.</t>
    </note>
  </front>
  <middle>
    <section anchor="introduction" numbered="true" toc="default">
      <name>Introduction</name>
      <t>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.</t>
      <t>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.</t>
      <t>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 <xref target="positionpapers" format="default"/>.
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.</t>
      <t>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 <xref target="participants" format="default"/>.</t>
      <t>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.</t>
    </section>
    <section anchor="scope" numbered="true" toc="default">
      <name>Scope</name>
      <t>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.</t>
      <t>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.</t>
      <t>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.</t>
      <t>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.</t>
      <t>The scope of this workshop, based on the call for contributions, included:</t>
      <ul spacing="normal">
        <li>measurements about traffic changes, user experience and problems, service performance, and other relevant aspects</li>
        <li>discussion about the behind the scenes network management and expansion activities</li>
        <li>experiences in the fields of general Internet connectivity, conferencing, media/entertainment, and Internet infrastructure</li>
        <li>lessons learned for preparedness and operations</li>
        <li>lessons learned for Internet technology and architecture</li>
      </ul>
    </section>
    <section anchor="discussion-topics" numbered="true" toc="default">
      <name>Workshop Topics and Discussion</name>
      <section anchor="measurement" numbered="true" toc="default">
        <name>Measurement-based Observations on Network Traffic Dynamics</name>
        <t>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.</t>
        <t>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.</t>
        <t>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.</t>
        <t>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.</t>
        <section anchor="overall-traffic-growth" numbered="true" toc="default">
          <name>Overall Traffic Growth</name>
          <t>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 <xref target="Feldmann2020" format="default"/> 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.</t>
          <t>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.</t>
          <t>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.</t>
        </section>
        <section anchor="changes-in-application-use" numbered="true" toc="default">
          <name>Changes in Application Use</name>
          <t>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 <xref target="Feldmann2020" format="default"/>
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 Microsoft Teams.
For example, the relative traffic share of many "essential" applications like VPN and conferencing tools
increased by more than 200%.</t>
          <t>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.</t>
          <section anchor="example-campus-networks" numbered="true" toc="default">
            <name>Example Campus Networks</name>
            <t>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.</t>
            <t>Similar changes were observed by measuring REDIMadrid <xref target="Feldmann2020" format="default"/>, 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.</t>
            <t>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.</t>
          </section>
        </section>
        <section anchor="mobile-networks-and-mobility" numbered="true" toc="default">
          <name>Mobile Networks and Mobility</name>
          <t>Mobile network data usage appeared to decline following the imposition of localized 
lockdown measures, as these reduced typical levels of mobility and roaming.</t>
          <t><xref target="Lutu2020" format="default"/> 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.</t>
          <t>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.</t>
          <t>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.</t>
          <t>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.</t>
        </section>
        <section anchor="a-deeper-look-at-interconnections" numbered="true" toc="default">
          <name>A Deeper Look at Interconnections</name>
          <t>Traffic at points of network interconnection noticeably increased, but most operators 
reacted quickly by rapidly adding additional capacity <xref target="Feldmann2020" format="default"/>. 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.</t>
          <t>Measurements of interconnection links at major US ISPs by CAIDA and MIT found some evidence 
of diurnal congestion around the March 2020 timeframe <xref target="Clark2020" format="default"/>, 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.</t>
        </section>
        <section anchor="cloud-platforms" numbered="true" toc="default">
          <name>Cloud Platforms</name>
          <t>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 <xref target="Mok2020" format="default"/>.</t>
          <t>The key findings included:</t>
          <ul spacing="normal">
            <li>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.</li>
            <li>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.</li>
            <li>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.</li>
          </ul>
        </section>
        <section anchor="last-mile-congestion" numbered="true" toc="default">
          <name>Last-Mile Congestion</name>
          <t>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 <xref target="Fontugne2020-1" format="default"/>. 
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).</t>
          <t>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".</t>
        </section>
        <section anchor="user-behaviour" numbered="true" toc="default">
          <name>User Behaviour</name>
          <t>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% <xref target="NCTA2020" format="default"/> <xref target="Comcast2020" format="default"/>. Vodafone reported that upstream
traffic grew 100% in some markets <xref target="Vodafone2020" format="default"/>.</t>
          <t>Ericsson's Consumer Lab surveyed users for their usage and experiences
during the crisis. Some of the key findings in <xref target="ConsumerlabReport2020" format="default"/> were:</t>
          <ul spacing="normal">
            <li>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.</li>
            <li>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.</li>
            <li>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.</li>
          </ul>
          <t>Some of the behaviours are likely permanent changes
<xref target="ConsumerlabReport2020" format="default"/>. 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 <xref target="WorkplaceAnalytics2020" format="default"/> <xref target="McKinsey2020" format="default"/>.</t>
        </section>
      </section>
      <section anchor="operational" numbered="true" toc="default">
        <name>Operational Practices and Architectural Considerations</name>
        <t>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.</t>
        <section anchor="digital-divide" numbered="true" toc="default">
          <name>Digital Divide</name>
          <t>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.</t>
          <t>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 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.</t>
        </section>
        <section anchor="applications" numbered="true" toc="default">
          <name>Applications</name>
          <t>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.</t>
          <t>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.</t>
          <t>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.</t>
          <t>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.</t>
          <t>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).</t>
        </section>
        <section anchor="observability" numbered="true" toc="default">
          <name>Observability</name>
          <t>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?</t>
          <t>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.</t>
          <t>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.</t>
          <t>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.</t>
        </section>
        <section anchor="security" numbered="true" toc="default">
          <name>Security</name>
          <t>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.</t>
          <t>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<xref target="Kirsty2020" format="default"/>.</t>
          <t>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 <xref target="Kirsty2020" format="default"/>. 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.</t>
          <t>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<xref target="Kirsty2020" format="default"/>, 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.</t>
          <t>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.</t>
          <t>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?</t>
          <t>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.</t>
        </section>
        <section anchor="discussion" numbered="true" toc="default">
          <name>Discussion</name>
          <t>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.</t>
          <t>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.</t>
          <t>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.</t>
        </section>
      </section>
      <section anchor="conclusions" numbered="true" toc="default">
        <name>Conclusions</name>
        <t>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 that the shifts have
gone relatively smoothly from the point of view of overall consumer
experience.</t>
        <t>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.</t>
        <t>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.</t>
        <t>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.</t>
        <t>On the other hand, this is not to say that no improvements are needed:</t>
        <ul spacing="normal">
          <li>Improve observability to better understand 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.</li>
          <li>Maintaining 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 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.</li>
          <li>The pandemic has shown how the effects of the digital divide can be
amplified during a crisis. More attention is needed to ensure that
broadband is available to all, and that Internet services equally
serve different groups.</li>
          <li>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.</li>
          <li>Informal collaboration between different parties needs to continue
and be strengthened.</li>
        </ul>
      </section>
    </section>
    <section anchor="feedback-on-meeting-format" numbered="true" toc="default">
      <name>Feedback on Meeting Format</name>
      <t>While there are frequently virtual participants in IAB workshops, the
IAB had no experience running workshops entirely virtually.</t>
      <t>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).</t>
      <t>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.</t>
    </section>
    <section anchor="positionpapers" numbered="true" toc="default">
      <name>Position Papers</name>
      <t>The following position papers were received, in alphabetical order:</t>
      <ul spacing="normal">
        <li>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 <xref target="Afxanasyev2020" format="default"/></li>
        <li>Arkko, Jari: Observations on Network User Behaviour During COVID-19 <xref target="Arkko2020" format="default"/></li>
        <li>Bronzino, F., Culley, E., Feamster, N. Liu. S., Livingood. J., and Schmitt, P.: IAB COVID-19 Workshop: Interconnection Changes in the United States <xref target="Bronzino2020" format="default"/></li>
        <li>Campling, Andrew and Lazanski, Dominique: Will the Internet Still Be Resilient During the Next Black Swan Event? <xref target="Campling2020" format="default"/></li>
        <li>Cho, Kenjiro: On the COVID-19 Impact to broadband traffic in Japan <xref target="Cho2020" format="default"/></li>
        <li>Clark, D.: Measurement of congestion on ISP interconnection links <xref target="Clark2020" format="default"/></li>
        <li>Favale, T., Soro, F., Trevisan, M., Drago, I., and Mellia, M.: Campus traffic and e-Learning during COVID-19 pandemic <xref target="Favale2020" format="default"/></li>
        <li>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 <xref target="Feldmann2020" format="default"/></li>
        <li>Fontugne, R., Shah, A., and Cho, K.: The Impact of COVID-19 on Last-mile Latency <xref target="Fontugne2020" format="default"/></li>
        <li>Gillmor, D.: Vaccines, Privacy, Software Updates, and Trust <xref target="Gillmor2020" format="default"/></li>
        <li>Gu, Y. and Li, Z. Covid 19 Impact on China ISP's Network Traffic Pattern and Solution Discussion <xref target="Gu2020" format="default"/></li>
        <li>Jennings, C. and Kozanian, P.: WebEx Scaling During Covid <xref target="Jennings2020" format="default"/></li>
        <li>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 <xref target="Lutu2020" format="default"/></li>
        <li>Mok, Ricky, and claffy, kc: Measuring the impact of COVID-19 on cloud network performance <xref target="Mok2020" format="default"/></li>
        <li>Kirsty P: IAB COVID-19 Network Impacts <xref target="Kirsty2020" format="default"/></li>
      </ul>
    </section>
    <section anchor="participants" numbered="true" toc="default">
      <name>Workshop participants</name>
      <t>The following is an alphabetical list of participants in the workshop.</t>
      <ul spacing="normal">
        <li>Jari Arkko (Ericsson/IAB)</li>
        <li>Ben Campbell (Independent/IAB)</li>
        <li>Andrew Campling (419 Consulting)</li>
        <li>Kenjiro Cho (IIJ)</li>
        <li>kc Claffy (CAIDA)</li>
        <li>David Clark (MIT CSAIL)</li>
        <li>Chris Dietzel (DE-CIX)</li>
        <li>Idilio Drago (University of Turin)</li>
        <li>Stephen Farrell (Trinity College Dublin/IAB)</li>
        <li>Nick Feamster (University of Chicago)</li>
        <li>Anja Feldmann (Max Planck Institute for Informatics)</li>
        <li>Romain Fontugne (IIJ Research Lab)</li>
        <li>Oliver Gasser (Max Planck Institute for Informatics)</li>
        <li>Daniel Kahn Gillmor (ACLU)</li>
        <li>Yunan Gu (Huawei)</li>
        <li>Oliver Hohlfeld (Brandenburg University of Technology, BTU)</li>
        <li>Jana Iyengar (Fastly)</li>
        <li>Cullen Jennings (Cisco/IAB)</li>
        <li>Mirja Kuhlewind (Ericsson/IAB)</li>
        <li>Franziska Lichtblau (Max Planck Institute for Informatics)</li>
        <li>Dominique Lazanski</li>
        <li>Zhenbin Li (Huawei/IAB)</li>
        <li>Jason Livingood (Comcast)</li>
        <li>Andra Lutu (Telefonica Research)</li>
        <li>Vesna Manojlovic (RIPE NCC)</li>
        <li>R Martin EC (?)</li>
        <li>Matt Matthis (Google)</li>
        <li>Larry Masinter (Retired)</li>
        <li>Jared Mauch (Akamai/IAB)</li>
        <li>Deep Medhi (NSF)</li>
        <li>Marco Mellia (Politecnico di Torino)</li>
        <li>Ricky Mok (CAIDA)</li>
        <li>Karen O'Donoghue (Internet Society)</li>
        <li>Kirsty P (NCSC)</li>
        <li>Diego Perino (Telefonica Research)</li>
        <li>Colin Perkins (University of Glasgow/IRTF/IAB)</li>
        <li>Enric Pujol (Benocs)</li>
        <li>Anant Shah (Verizon Media Platform)</li>
        <li>Francesca Soro (Politecnico di Torino)</li>
        <li>Brian Trammell (Google)</li>
        <li>Gergios Tselentis (European Commission)</li>
        <li>Martino Trevisan</li>
        <li>Lan Wang (University of Memphis)</li>
        <li>Rob Wilton (Cisco)</li>
        <li>Jiankang Yao (CNNIC)</li>
        <li>Lixia Zhang (UCLA)</li>
      </ul>
    </section>
    <section anchor="program-committee" numbered="true" toc="default">
      <name>Program Committee</name>
      <t>The workshop Program Committee members were Jari Arkko, Stephen Farrell, Cullen
Jennings, Colin Perkins, Ben Campbell, and Mirja Kuehlewind.</t>
    </section>
    <section anchor="acknowledgments" numbered="true" toc="default">
      <name>Acknowledgments</name>
      <t>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.</t>
      <t>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.</t>
    </section>
  </middle>
  <back>
    <references>
      <name>Informative References</name>
      <reference anchor="Afxanasyev2020">
        <front>
          <title>Identifying the Disease from the Symptoms: Lessons for Networking in the COVID-19 Era</title>
          <author initials="A." surname="Afxanasyev">
            <organization/>
          </author>
          <author initials="L." surname="Wang">
            <organization/>
          </author>
          <author initials="E." surname="Yeh">
            <organization/>
          </author>
          <author initials="B." surname="Zhang">
            <organization/>
          </author>
          <author initials="L." surname="Zhang">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/12/IAB-COVID-19-WS_102820.pdf" value=""/>
      </reference>
      <reference anchor="Arkko2020">
        <front>
          <title>Observations on Network User Behaviour During COVID-19</title>
          <author initials="J." surname="Arkko">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-arkko.pdf" value=""/>
      </reference>
      <reference anchor="Bronzino2020">
        <front>
          <title>IAB COVID-19 Workshop: Interconnection Changes in the United States</title>
          <author initials="F." surname="Bronzino">
            <organization/>
          </author>
          <author initials="E." surname="Culley">
            <organization/>
          </author>
          <author initials="N." surname="Feamster">
            <organization/>
          </author>
          <author initials="S." surname="Liu">
            <organization/>
          </author>
          <author initials="J." surname="Livingood">
            <organization/>
          </author>
          <author initials="P." surname="Schmitt">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-feamster.pdf" value=""/>
      </reference>
      <reference anchor="Campling2020">
        <front>
          <title>Will the Internet Still Be Resilient During the Next Black Swan Event?</title>
          <author initials="A." surname="Campling">
            <organization/>
          </author>
          <author initials="D." surname="Lazanski">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-campling.pdf" value=""/>
      </reference>
      <reference anchor="Cho2020">
        <front>
          <title>On the COVID-19 Impact to broadband traffic in Japan</title>
          <author initials="K." surname="Cho">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-cho.pdf" value=""/>
      </reference>
      <reference anchor="Clark2020">
        <front>
          <title>Measurement of congestion on ISP interconnection links</title>
          <author initials="D." surname="Clark">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-clark.pdf" value=""/>
      </reference>
      <reference anchor="Favale2020">
        <front>
          <title>Campus traffic and e-Learning during COVID-19 pandemic</title>
          <author initials="T." surname="Favale">
            <organization/>
          </author>
          <author initials="F." surname="Soro">
            <organization/>
          </author>
          <author initials="M." surname="Trevisan">
            <organization/>
          </author>
          <author initials="I." surname="Drago">
            <organization/>
          </author>
          <author initials="M." surname="Mellia">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-favale.pdf" value=""/>
      </reference>
      <reference anchor="Feldmann2020">
        <front>
          <title>A view of Internet Traffic Shifts at ISP and IXPs during the COVID-19 Pandemic</title>
          <author initials="A." surname="Feldmann">
            <organization/>
          </author>
          <author initials="O." surname="Gasser">
            <organization/>
          </author>
          <author initials="F." surname="Lichtblau">
            <organization/>
          </author>
          <author initials="E." surname="Pujol">
            <organization/>
          </author>
          <author initials="I." surname="Poese">
            <organization/>
          </author>
          <author initials="C." surname="Dietzel">
            <organization/>
          </author>
          <author initials="D." surname="Wagner">
            <organization/>
          </author>
          <author initials="M." surname="Wichtlhuber">
            <organization/>
          </author>
          <author initials="J." surname="Tapiador">
            <organization/>
          </author>
          <author initials="." surname="N Vallina-Rodriguez">
            <organization/>
          </author>
          <author initials="O." surname="Hohlfeld">
            <organization/>
          </author>
          <author initials="G." surname="Smaragdakis">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-feldmann.pdf" value=""/>
      </reference>
      <reference anchor="Fontugne2020">
        <front>
          <title>The Impact of COVID-19 on Last-mile Latency</title>
          <author initials="R." surname="Fontugne">
            <organization/>
          </author>
          <author initials="A." surname="Shah">
            <organization/>
          </author>
          <author initials="K." surname="Cho">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-fontugne.pdf" value=""/>
      </reference>
      <reference anchor="Gillmor2020">
        <front>
          <title>Vaccines, Privacy, Software Updates, and Trust</title>
          <author initials="D." surname="Gillmor">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-gillmor.pdf" value=""/>
      </reference>
      <reference anchor="Gu2020">
        <front>
          <title>Covid 19 Impact on China ISP's Network Traffic Pattern and Solution Discussion</title>
          <author initials="Y." surname="Gu">
            <organization/>
          </author>
          <author initials="Z." surname="Li">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-gu.pdf" value=""/>
      </reference>
      <reference anchor="Jennings2020">
        <front>
          <title>WebEx Scaling During Covid</title>
          <author initials="C." surname="Jennings">
            <organization/>
          </author>
          <author initials="P." surname="Kozanian">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-jennings.pdf" value=""/>
      </reference>
      <reference anchor="Lutu2020">
        <front>
          <title>A Characterization of the COVID-19 Pandemic Impact on a Mobile Network Operator Traffic</title>
          <author initials="A." surname="Lutu">
            <organization/>
          </author>
          <author initials="D." surname="Perino">
            <organization/>
          </author>
          <author initials="M." surname="Bagnulo">
            <organization/>
          </author>
          <author initials="E." surname="Frias-Martinez">
            <organization/>
          </author>
          <author initials="J." surname="Khangosstar">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-lutu.pdf" value=""/>
      </reference>
      <reference anchor="Mok2020">
        <front>
          <title>Measuring the impact of COVID-19 on cloud network performance</title>
          <author initials="R." surname="Mok">
            <organization/>
          </author>
          <author initials="." surname="kc claffy">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-mok.pdf" value=""/>
      </reference>
      <reference anchor="Kirsty2020">
        <front>
          <title>IAB COVID-19 Network Impacts</title>
          <author initials="." surname="Kirsty P">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="https://www.iab.org/wp-content/IAB-uploads/2020/10/covid19-kirstyp.pdf" value=""/>
      </reference>
      <reference anchor="Comcast2020">
        <front>
          <title>COVID-19 Network Update</title>
          <author initials="." surname="Comcast">
            <organization/>
          </author>
          <date year="2020" month="May"/>
        </front>
        <seriesInfo name="https://corporate.comcast.com/covid-19/network/may-20-2020" value=""/>
      </reference>
      <reference anchor="NCTA2020">
        <front>
          <title>COVID-19: How Cable's Internet Networks Are Performing: Metrics, Trends &amp; Observations</title>
          <author initials="." surname="NCTA">
            <organization/>
          </author>
          <date year="2020"/>
        </front>
        <seriesInfo name="https://www.ncta.com/COVIDdashboard" value=""/>
      </reference>
      <reference anchor="Vodafone2020">
        <front>
          <title>An update on Vodafone's networks</title>
          <author initials="." surname="Vodafone">
            <organization/>
          </author>
          <date year="2020" month="April"/>
        </front>
        <seriesInfo name="https://www.vodafone.com/covid19/news/update-on-vodafone-networks" value=""/>
      </reference>
      <reference anchor="ConsumerlabReport2020">
        <front>
          <title>Keeping consumers connected in a COVID-19 context</title>
          <author initials="." surname="Ericsson Consumer &amp; IndustryLab">
            <organization/>
          </author>
          <date year="2020" month="June"/>
        </front>
        <seriesInfo name="https://www.ericsson.com/en/reports-and-papers/consumerlab/reports/keeping-consumers-connected-during-the-covid-19-crisis" value=""/>
      </reference>
      <reference anchor="WorkplaceAnalytics2020">
        <front>
          <title>Work-At-Home After Covid-19—Our Forecast</title>
          <author initials="K." surname="Lister">
            <organization/>
          </author>
          <date year="2020"/>
        </front>
        <seriesInfo name="https://globalworkplaceanalytics.com/work-at-home-after-covid-19-our-forecast" value=""/>
      </reference>
      <reference anchor="McKinsey2020">
        <front>
          <title>Reimagining the office and work life after COVID-19</title>
          <author initials="B." surname="Boland">
            <organization/>
          </author>
          <author initials="A." surname="De Smet">
            <organization/>
          </author>
          <author initials="R." surname="Palter">
            <organization/>
          </author>
          <author initials="A." surname="Sanghvi">
            <organization/>
          </author>
          <date year="2020" month="June"/>
        </front>
        <seriesInfo name="https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/Organization/Our%20Insights/Reimagining%20the%20office%20and%20work%20life%20after%20COVID%2019/Reimagining-the-office-and-work-life-after-COVID-19-final.pdf" value=""/>
      </reference>
      <reference anchor="Fontugne2020-1">
        <front>
          <title>Persistent Last-mile Congestion: Not so Uncommon</title>
          <author initials="R." surname="Fontugne">
            <organization/>
          </author>
          <author initials="A." surname="Shah">
            <organization/>
          </author>
          <author initials="K." surname="Cho">
            <organization/>
          </author>
          <date year="2020" month="October"/>
        </front>
        <seriesInfo name="Proceedings of the ACM Internet Measurement Conference (IMC '20)" value=""/>
      </reference>
    </references>
  </back>
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