Network Working Group

Internet Architecture Board (IAB)                               J. Arkko
Internet-Draft                                                  Ericsson
Intended status: Informational
Request for Comments: 9075                                    S. Farrell
Expires: 6 November 2021                          Trinity College Dublin
Category: Informational                                     M. Kühlewind
                                                                Ericsson
ISSN: 2070-1721                                               C. Perkins
                                                   University of Glasgow
                                                              5 May
                                                               July 2021

       Report from the IAB COVID-19 Network Impacts Workshop 2020
                     draft-iab-covid19-workshop-03

Abstract

   The COVID-19 Coronavirus disease (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 ongoing travel
   and contact restrictions at that time.

Discussion Venues

   This note

   Note that this document is to be removed before publishing as an RFC.

   Source for a report on the proceedings of the
   workshop.  The views and positions documented in this draft report are
   those of the workshop participants and an issue tracker can be found at
   https://github.com/intarchboard/covid19-workshop. do not necessarily reflect IAB
   views and positions.

Status of This Memo

   This Internet-Draft document is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents not an Internet Standards Track specification; it is
   published for informational purposes.

   This document is a product of the Internet Engineering
   Task Force (IETF).  Note Architecture Board (IAB)
   and represents information that other groups may also distribute
   working documents as Internet-Drafts.  The list the IAB has deemed valuable to
   provide for permanent record.  It represents the consensus of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts the
   Internet Architecture Board (IAB).  Documents approved for
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   This Internet-Draft will expire on 6 November 2021.
   https://www.rfc-editor.org/info/rfc9075.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Workshop Topics and Discussion  . . . . . . . . . . . . . . .   5
     3.1.  Measurement-based  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 Behavior
     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.
   7.  Informative References  . . . . . . . . . . . . . . . . . . .  21
   Appendix A.  Workshop Participants
   IAB Members at the Time of Approval
   Acknowledgments
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  24

1.  Introduction

   The Internet Architecture Board (IAB) held a workshop to discuss
   network impacts of the COVID-19 pandemic, 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
   ongoing travel and contact restrictions at that time.

   COVID-19 has caused changes in user behavior, which in turn drove
   change to
   changes in 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 in Internet traffic in terms of
   volumes, volume and
   location, as well as shifts in the type types of applications used.  This
   shift in traffic as well as and user behavior created also created a shift in security partices
   practices as well as attack patterns that made use of the attack surface
   surface, resulting from the shift to home-working working from home in a global
   crisis.

   Announcement

   An announcement for the workshop was sent out in July 2020, 2020 requesting
   that interested parties to submit position papers for to the workshop
   program committee.  A total of 15 position papers were received from
   altogether
   33 authors. authors in total.  The papers are listed in Section 5.  In
   addition, several other types of contributions and pointers to
   existing work were provided.  A number of position papers referred to
   parallel work being published in measurement-related academic
   conferences.

   Invitations for the workshop were sent out based on the position
   papers and other expressions of interest.  On the workshop conference
   calls were 45 46 participants, listed in Section 6. Appendix A.

   The workshop was held over the course of one week hosting and hosted three
   sessions covering i) measurements and observations, ii) operational
   and security issues, and iii) future consideration and conclusions.
   As these three sessions were scheduled on Monday, Wednesday, and Friday
   Friday, a positive side effect was that the time in between could the
   sessions could be used for mailing list discussion and compilation of
   additional workshop material.

2.  Scope

   The COVID-19 pandemic has had a tremendous impact on people's lives
   and the
   as well as societies and economies around the globe.  But it also had
   a big impact on networking.  With large numbers of people working
   from home or otherwise depending on the network for their daily
   lives, network traffic volume has surged.  Internet service providers
   and operators have reported a 20% traffic growth or more traffic growth in a matter of
   weeks.  Traffic at Internet Exchange Points (IXPs) is similarly on
   the rise.  Most forms of network traffic have seen an increase, with
   conversational multimedia traffic growing growing, in some cases cases, by more
   than 200%. And user time spent on conferencing services has risen by
   an order of magnitude on some conferencing platforms.

   In general, the Internet has coped relatively well with this traffic
   growth.  The situation is not perfect: there has have also been some
   outages, video quality reduction, and other issues.  Nevertheless, it
   is interesting to see how the technology, operators operators, and service
   providers have been able to respond to large changes in traffic
   patterns.

   Understanding what actually happened with Internet traffic is is, of
   course
   course, interesting by in its own right.  How that impacted the user
   experience or the intended function of the services is equally
   interesting.  Measurements of and reports on Internet traffic in 2020
   are therefore valuable.  But it would also be interesting to
   understand what types of network management and capacity expansion
   actions were taken in general.  Anecdotal evidence points to Internet
   and service providers tracking how their services are used, and used and, in
   many cases cases, adjusting services to accommodate the new traffic
   patterns, from dynamic allocation of compute computing resources to more
   complex changes.

   The impacts of this crisis are also a potential opportunity to
   understand the impact of traffic shifts and growth more generally, or generally to
   prepare for future situations -- crises or otherwise - -- that impact
   networking.  Or even
   networking, or to allow us to adjust the technology to be even better
   suited to respond to changes.

   The scope of this workshop, based on the call for contributions,
   included:

   *  measurements about of traffic changes, user experience and problems,
      service performance, and other relevant aspects

   *  discussion about the behind the scenes behind-the-scenes network management and
      expansion activities

   *  sharing experiences in the fields of general Internet
      connectivity, conferencing, media/entertainment, and Internet
      infrastructure

   *  lessons learned for on preparedness and operations

   *  lessons learned for on Internet technology and architecture

3.  Workshop Topics and Discussion

3.1.  Measurement-based  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 data, and
   these submissions provided a good basis get for a better understanding of
   the situation, covering different angles and aspects of network
   traffic and kind different kinds of networks.

   Changes in Internet traffic due to the COVID-19 pandemic affected
   different networks in various ways.  Yet all networks observed saw some form
   of change, be it a reduction in traffic, an increase in traffic, a
   change in working days workday and weekend days diurnal patterns, or a change in
   traffic classes.  Traffic volume, directionality ratios, and its
   source traffic
   origins and destination are destinations were radically different than from before
   COVID-19.

   At a high level, while traffic from home networks increased
   significantly, for the traffic in mobile networks different trends
   were observed.  Either the traffic increased as well -- for instance,
   in locations where use of residential ISP services is less common --
   traffic decreased as a result of reduced population mobility.  The  This
   observed behavior traffic decrease in mobile networks is antagonistic, yet complementary, to reflected rather the one observed in
   residential ISPs.  In residential networks there
   opposite trend than what 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 points as well in certain
   last mile network
   last-mile networks was reported, mainly in March, no persitent persistent
   congestion was observed.  Further, a downward trends trend in download
   throughput to certain cloud regions was measured, which can probably
   be explained with by the increase increased use of cloud services.  This gives
   another indication that the scalng scaling of shared resources in the
   Internet is working reasonably well enough to handle even larger
   changes in traffic as experience experienced during the first nearly global
   lockdown of the COVID-19 pandemic.

3.1.1.  Overall Traffic Growth

   The global pandemic has significantly accelerated the growth of data
   traffic worldwide.  Based on the measurement data of one ISP, three
   IXPs, a metropolitan educational network, and a mobile operator, it
   was observed at the beginning of the workshop [Feldmann2020] that
   overall that,
   overall, the network was able to handle the situation well, well despite a
   significant and sudden increase in the traffic growth rate in March
   and April.  That is, after the lockdown was implemented in March, a
   traffic increase of 15-20% was observed at the ISP as well as at the
   three IXPs was
   observed.  That represents the IXPs.  This traffic growth expected in a typical
   year growth, which now would typically occur over a
   year, took place in the matter of over a few weeks only---a -- a substantial increase.  At DE-CIX DE-
   CIX Frankfurt, the world's largest Internet Exchange Point in terms
   of data throughput, the year 2020
   has seen saw the largest increase in peak
   traffic within a single year since the IXP was founded in 1995.
   Additionally, mobile traffic has slightly receded.  In access
   networks, the growth rate of upstream traffic also exceeded the
   growth in downstream traffic, reflecting increased adoption and use
   of video conferencing videoconferencing and other remote work and school applications.

   Most traffic increases happened during non-traditional outside of pre-pandemic peak hours: hours.
   Before the first COVID-19 lockdowns, the main time of use was in the
   evening hours during the week, whereas whereas, since March 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. (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: absorbed, either by using existing reserve capacity, 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 resume some of their daily habits activities outside
   of their home again, as expected, there was a decrease of in the traffic
   observed at the IXPs and the ISP; instead 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 networks, it was
   observed [Feldmann2020] that traffic associated with web
   conferencing, video, and gaming increased largely significantly in March 2020
   as a result of the increasing user demand for solutions like Zoom or
   Microsoft Teams.  For example, the relative traffic share of many
   "essential" applications like VPN and conferencing tools increased by
   more than 200%.

   Also, as people spent more hours at home, they tended to watch videos
   or play games, thus increasing entertainment traffic demands.  At the
   same time, the traffic share for other traffic classes decreased
   substantially, e.g., traffic related to education, social media, and
   ---for and,
   for some periods---CDNs. periods, content delivery networks (CDNs).  In April and
   June, web conferencing traffic was still high compared to the pre-pandemic pre-
   pandemic scenario, while a slight decrease in CDN and social media
   traffic was observed.  During these months 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. social activities.

3.1.2.1.  Example Campus Networks

   Changes in traffic have been observed at University 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,
   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 not, however, lead to noticeable
   performance impairments, nor have has significantly poor performance been
   observed for in students in remote regions of Italy.  Outgoing traffic
   also increased due to other remote working solutions, such as
   collaboration platforms, VPNs, and remote desktops.

   Similar changes were observed by measuring REDIMadrid [Feldmann2020],
   a European educational and research network, which network that connects 16
   independent universities and research centers in the metropolitan
   region of Madrid.  A drop of up to 55% in traffic volume on working
   days during the pandemic was observed.  Similar to findings for ISP/
   IXP networks, it was observed that working days and weekend days are
   becoming more similar in terms of total traffic.  The hourly traffic
   patterns reveal a traffic increase between 9 pm and 7 am.  This could
   be due to users working more frequently at unusual times, times but could
   also potentially be caused by overseas students (mainly from Latin
   America and East Asia as suggested by the AS Autonomous System (AS)
   numbers from which these connections came from) came) who accessed university
   network resources from their home countries.

   Given the fact that the users of the academic network (e.g., students
   and research staff) had to leave the campus as a response to lockdown
   measures, also the traffic in and out in-and-out (i.e., ingress and egress) ratio
   also changed drastically.  Prior to the lockdown, the incoming
   traffic volume was much larger then than the outgoing traffic. traffic volume.
   This changed to a more balanced ratio.  This change of traffic
   asymmetry can be explained by the nature of remote work.  On the one end,
   hand, users connected to the network services mainly to access
   resources, hence the increase in outgoing traffic.  On the other end,
   hand, all external (i.e., Internet-based) resources requested during
   work were no longer accessed from the educational network but from
   the users' homes.

3.1.3.  Mobile Networks and Mobility

   Mobile network data usage appeared to decline following the
   imposition of localized lockdown measures, 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 signaling information regarding users' device
   mobility activity, they observed a decrease of 50% in mobility
   (according to different mobility metrics) in the UK during the
   lockdown period.  As they found no correlation between this reduction
   in mobility and the number of confirmed COVID-19 cases, only the
   enforced government order was effective in significantly reducing
   mobility
   mobility, and this reduction was more significant in densely
   populated urban areas than in rural areas.  For London, 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 the traffic
   patterns of the cellular network.  The downlink data traffic volume
   aggregated for all bearers (including conversational voice) decreased
   for all the entire UK by up to 25% during the lockdown period.  This
   correlates with the reduction in mobility that was observed country-wide,
   countrywide, which likely resulted in people relying more on broadband
   residential broadband Internet access to run download intensive 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, order was enacted, further corroborates the
   drop in cellular connectivity usage.

   The total uplink data traffic volume, on the other hand, experienced
   little changes change (between -7% and +1,5%) +1.5%) during lockdown.  This was
   mainly due to the increase of 4G voice traffic (i.e., VoLTE) Voice over LTE
   (VoLTE)) across the UK that peaked at 150% after the lockdown
   compared to the national medial median value before the pandemic, thus
   compensating for the decrease in data traffic in the uplink.

   Finally, it was also observed that mobility changes have a different
   impact on network usage in geodemographic area clusters.  In densely
   populated urban areas, a significantly higher decrease of mobile
   network usage (i.e., downlink and uplink traffic volumes, volume, radio load load,
   and active users) was observed than in compared to rural areas.  In the case
   of London, this was likely due to the geodemographics of the central
   districts, which include many seasonal residents (e.g., tourists), tourists) and
   business and commercial areas.

3.1.4.  A Deeper Look at Interconnections

   Traffic at points of network interconnection noticeably increased,
   but most operators reacted quickly by rapidly adding additional
   capacity [Feldmann2020].  The amount of increases increase varied, with some
   networks that hosted popular applications such as video conferencing videoconferencing
   experiencing traffic growth of several hundred to several thousand
   percent.  At the IXP-level, 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 the Center
   for Applied Internet Data Analysis (CAIDA) and
   MIT the Massachusetts
   Institute of Technology (MIT) found some evidence of diurnal
   congestion around the March 2020
   timeframe time frame [Clark2020], but most of
   this congestion disappeared in a few weeks, which suggests that
   operators indeed took steps to add capacity or otherwise mitigate the
   congestion.

3.1.5.  Cloud Platforms

   Cloud infrastructure played a key role in supporting bandwidth-
   intensive video conferencing videoconferencing and remote learning tools to practise practice
   social distancing during the COVID-19 pandemic.  Network congestion
   between cloud platforms and access networks could impact the quality
   of experience of these cloud-based applications.  CAIDA leveraged
   web-based speed test servers to perform take download and upload throughput
   measurements from virtual machines in public cloud platforms to
   various access ISPs in the United States [Mok2020].

   The key findings included: included the following:

   *  Persistent congestion events were not widely observed between
      cloud platforms and these networks, particular for large-scale
      ISPs, but we could observe large diurnal download throughput
      variations in peak hours from some locations to the cloud.

   *  There was evidence of persistent congestion in the egress
      direction to regional ISPs serving suburban areas in the U.S. US.
      Their users could have suffered from poor video streaming or file
      download performance from the cloud.

   *  The macroscopic analysis over 3 months (June-August, (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 Internet Measurement Conference (IMC '20)
   research paper paper, Fontugne et al. investigated last-mile latency using
   traceroute data from RIPE Reseaux IP Europeens (RIPE) Atlas probes located
   in 646 ASes and looked for recurrent performance degradation
   [Fontugne2020-1].  They found that that, in normal times times, Atlas probes in only 10% ASes
   experience persistent last-mile congestion, congestion in only 10% of ASes, but
   they recorded 55% more congested ASes during the COVID-19 outbreak.
   This deterioration caused by stay-at-home measures is particularly
   marked in networks with a very large number of users and in certain
   parts of the world.  They found Japan to be the most impacted country
   in their study study, looking specifically at NTT OCN, the Nippon Telegraph and
   Telephone (NTT) Corporation Open Computer Network (OCN) but noting
   similar observations for several Japanese networks, including IIJ
   Internet Initiative Japan (IIJ) (AS2497).

   From mid-2020 onwards, onward, however, 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
   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,
   Internet; as Nietzsche wrote, "What does not kill me makes me
   stronger".

3.1.7.  User Behaviour Behavior

   The type of traffic needed by the users also changed in 2020.
   Upstream traffic increased due the use of video conferences, videoconferences, remote
   schooling, and similar applications.  The NCTA National Cable &
   Telecommunications Association (NCTA) and Comcast reported that while
   downstream traffic grew 20%, upstream traffic grew by as much as 30% to 37%
   30-37% [NCTA2020] [Comcast2020].  Vodafone reported that upstream
   traffic grew by 100% in some markets [Vodafone2020].

   Ericsson's Consumer Lab ConsumerLab surveyed users for regarding their usage and
   experiences during the crisis.  Some of the key findings in
   [ConsumerlabReport2020] were: were as follows:

   *  9 in 10 users increased Internet activities, and time spent
      connected increased.  In addition, 1 in 5 started new online
      activities,
      activities; many in the older generation felt that they were
      helped by video calling, calling; parents felt that their children's
      education was helped, 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 responsibility for network operators.

   *  Smartphone application usage changed, with the fastest growth in
      apps related to COVID-19 tracking and information, remote working,
      e-learning, wellness, education, remote health consultation, and
      social shared experience applications.  Biggest  The biggest decreases were
      in travel and booking, ride hailing, location, and parking
      applications.

   Some of the behaviours behaviors are likely permanent changes
   [ConsumerlabReport2020].  The adoption of video calls and other new
   services by many consumers, such as the older generation, is likely
   going to have a long-lasting effect.  Surveys in various
   organizations point to a likely long-term increase in the number of
   people interested in remote work [WorkplaceAnalytics2020]
   [McKinsey2020].

3.2.  Operational Practices and Architectural Considerations

   The second and third day days of the workshop were held based focused on more open discussions focussed on
   of arising operational issues and the architectural issues arising or other and the conclusions
   that could be reached. reached from previous discussions and other issues
   raised in the position papers.

3.2.1.  Digital Divide

   Measurements from Fastly confirmed that Internet traffic volume, volume in
   multiple countries, countries rose rapidly at the same time as while COVID cases
   increased were increasing and
   lockdown policies came were coming into effect.  Download speeds also decreased,
   decreased but in a much less dramatic fashion than when overall
   bandwidth usage increased.  School closures led to a dramatic
   increase in traffic volume in many regions, and other public policy
   announcements triggered large traffic shifts.  This suggests that
   governments might usefully should coordinate with operators to allow time for pre-emptive
   preemptive operational changes, changes in some cases.

   Measurements from the US showed that download rates correlate with
   income levels.  However, download rates in the lowest income zip
   codes increased as the pandemic progressed, closing the divide with
   higher income areas.  One possible reason for this in the data is
   decisions by some ISPs, such as Comcast and Cox, that increased
   speeds for users on lower-cost certain lower-cost plans and in certain areas.
   This suggests that network capacity was available, available and that the
   correlation between income and download rates was not necessarily due
   to differences in the deployed infrastructure in different regions; regions,
   although it was noted that certain access link technologies provide
   more flexibility than others in this regard.

3.2.2.  Applications

   The web

   Web conferencing systems (e.g., Microsoft Teams, Zoom, Webex) saw
   incredible growth, with overnight traffic increases of 15-20% in
   response to public policy changes, such as lockdowns.  This required
   significant and rapid changes in infrastructure provisioning.

   Major video providers (YouTube, etc.) reduced bandwidth by 25% in
   some regions.  It was suggested that this had a huge impact on the
   quality of videoconferencing systems until networks could scale to
   handle the full bit-rate, bit rate, but other operators of some other services
   saw limited impact.

   Updates to popular games has have a significant impact on network load.
   Some discussions were reported between ISPs, CDNs, and the gaming
   industry on possibly coordinating various high-bandwidth update
   events, similar to what was done for entertainment/video download
   speeds.  There was an apparently difficult interplay between bulk
   download and interactive real-time applications, potentially due to
   buffer bloat and queuing delays.

   It was noted that operators have experience of with rapid growth of
   Internet traffic.  New applications with exponential growth are not
   that unusual in the network, and the traffic spike due to the
   lockdown was not that unprecedented for many.  Many operators have
   tools and mechanisms to deal with this.  Ensuring that knowledge if is
   shared is a challenge.

   Following these observations observations, traffic prioritisation prioritization was discussed,
   starting from DSCP marking, basically wondering if Differentiated Services Code Point (DSCP) marking.  The
   question arose as to whether a minimal priority
   marking priority-marking scheme would
   have helped during the pandemic, e.g. e.g., by allowing marking of less-than-best-effort less-
   than-best-effort traffic.  That discussion quickly devolved into a
   more general QoS and observability
   discussion, and discussion and, as such such, also touching
   touched on the effects of increased encryption.  The group was not,
   unsurprisingly, able to resolve the different perspectives and
   interests involved in that, involved, but the discussion demonstrated that progress is made (and being less
   heated). was
   made.

3.2.3.  Observability

   It is clear that there is a contrast in experience.  Many operators
   reported few problems, problems in terms of metrics metrics, such as measured download
   bandwidth, while video conferencing videoconferencing applications experienced
   significant usability problems running on those networks.  The
   interaction between application providers and network providers
   worked very smoothly to resolve these issues, supported by strong
   personal contacts and relationships.  But it seems clear that the
   metrics used by many operators to understand their network
   performance don't fully capture the impact on certain applications,
   and there is an observability gap.  Do we need more tools to figure
   out the various impacts on user experience?

   These types of applications use surprising amounts of Forward Error
   Correction (FEC).  Applications hide lots of loss to ensure a good
   user experience.  This makes it harder to observe problems.  The
   network can be behaving poorly, but the experience can be good
   enough.  Resiliency measures can improve the user experience but hide
   severe problems.  There may be a missing feedback loop between
   application developers and operators.

   It's clear that it's difficult for application providers and
   operators to isolate problems.  Is a problem due to the local WiFi, Wi-Fi,
   the access network, the cloud network, etc.?  Metrics from access
   points would help, but in general general, lack of observability into the
   network as a whole is a real concern when it comes to debugging
   performance issues.

   Further, it's clear that it can be difficult to route problem reports
   to the person who can fix them, especially if the reported
   information needs to be shared across multiple networks in the
   Internet.  COVID-enhanced cooperation made it easier to debug
   problems; lines of communication are important.

3.2.4.  Security

   The increased threats and network security impacts arising from
   COVID-19 fall into two areas: (1) the agility of malicious actors to
   spin up new campaigns using COVID-19 as a lure, and (2) the increased
   threat surface from a rapid shift towards home working. working from home.

   During 2020, there was a shift to home working generally, and in the
   way in which people use used the network, with network.  IT departments rolling rolled out new
   equipment quickly and using used technologies like VPNs for the first time,
   while others put existing solutions under much greater load.  As VPN
   technology became more widespread and more widely used, it arguably
   became a more valuable target; one Advanced Persistent Threat group
   (APT29) was successful in using recently published exploits in a
   range of VPN software to gain initial footholds[Kirsty2020]. footholds [Kirsty2020].

   Of all scams detected by the UK NCSC (United United Kingdom National Cyber Security Centre)
   Centre (UK NCSC) that purported to originate from the UK Government,
   more related to COVID-19 than any other subject.  There are other
   reports of a strong rise in phishing, fraud, and scams related to
   COVID [Kirsty2020].  Although, from the data seen to date,  Although the overall levels of cyber crime cybercrime have
   not increased, increased from the data seen to date, there was certainly a shift
   in activity - as both the NCSC and CISA (DHS the Department of Homeland Security
   Cybersecurity and Infrastructure Security Agency) Agency (DHS CISA) saw a
   growing use of COVID-19 related COVID-19-related themes by malicious cyber actors as a
   lure.  Attackers used COVID-19
   related COVID-19-related scams and phishing emails to target:
   target individuals, small and medium businesses, large organisations, organizations,
   and organisations organizations involved in both national and international
   COVID-19 responses (healthcare bodies, pharmaceutical companies, academia
   academia, and medical research
   organisations). organizations).  New targets, for example organisations targets (for
   example, organizations involved in COVID-19 vaccine development 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
   crowdsourced flagging of suspicious emails were found to be effective
   in
   the response to COVID-19-related scams[Kirsty2020], scams [Kirsty2020], and observing the
   DNS to detect malicious use is widespread and effective.  The use of
   DNS over HTTPS offers privacy benefits 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 have password
   training?  Or is there a fundamental problem with a technical
   solution?  Modern advice advocates a layered approach to security
   defences,
   defenses, with user education forming just one of those layers.

   Communication platforms such as Zoom are not new: many people have
   used them for years, but as COVID-19 saw an increasing number of
   organisations
   organizations and individuals turning to these technologies, they
   became an attractive target, target due to increased usage.  In turn, there
   was an increase in malicious cyber actor activity, either through
   hijacking online meetings that were not secured with passwords or
   leveraging unpatched software as an attack vector.  How can new or
   existing measures protect users from the attacks levied against the
   next vulnerable service?

   Overall, it may be that there were fewer security challenges than
   expected arising from many people suddenly working from home.
   However, the agility of attackers, the importance of robust and
   scalable defence defense mechanisms, and some existing security problems and
   challenges may have become even more obvious and acute with an
   increased use of Internet-based services, particularly in a pandemic
   situation and in times of uncertainty, where users can be more
   vulnerable to social engineering techniques and attacks.

3.2.5.  Discussion

   There is a concern that we're missing observability for the network
   as a whole.  Each application provider and operator has their own
   little lens.  No-one  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, shift and gives headroom for the network to cope.  The
   best effort
   best-effort nature of the network may help here.  Techniques  Using techniques to
   run the network closer to its limits improve performance in the usual
   case, usually improves performance,
   but highly optimised optimized networks may be less robust.

   Finally, it was observed that we get what we measure.  There may be
   an argument for operators to perhaps shift their measurement focus perhaps
   away from pure capacity, capacity to rather instead measure QoE Quality of Experience
   (QoE) or resilience.  The Internet is a critical infrastructure, and
   people are realising realizing that now.  We should use this as a wake-up-call wake-up call
   to improve resilience, both in protocol design and operational
   practice, not necessarily to
   optimise optimize for absolute performance or
   quality of experience.

3.3.  Conclusions

   There is a wealth of data about the performance of the Internet
   during the COVID-19 crisis.  The main conclusion from the various
   measurements is that fairly large shifts occurred.  And those shifts
   were not merely about changing exchanging one application for another, another; they
   actually impacted traffic flows and directions, directions and caused caused, in many cases
   cases, a significant traffic increase.  Early reports also seem to
   indicate that the shifts have gone relatively smoothly from the point
   of view of overall consumer experience.

   An important but not so visible factor that led to this running smoothly
   was that many people and organizations where were highly motivated to
   ensure good user experience.  A lot of collaboration happened in the
   background, problems were corrected, many providers significantly
   increased their capacity, and so on.

   On the security front, the COVID-19 crisis showcased the agility with
   which malicious actors can move in response to a shift in user
   Internet usage, usage and the vast potential of the disruption and damage
   that they can inflict.  Equally, it showed the agility of defenders, defenders
   when they have access to the tools and information they need to
   protect users and networks, and it showcased the power of Indicators
   of Compromise when defenders around the world are working together
   against the same problem.

   In general, the Internet also seems well suited for adapting to new
   situations, at least within some bounds.  The Internet is designed
   for flexibility and extensibility, rather than being optimized for
   today's particular traffic. traffic types.  This makes it possible to use it
   for many
   applications, applications and in many deployment situations, situations and to make
   changes as needed.  The generality is present in many parts of the
   overall system, from basic Internet technology to browsers, browsers and from
   name servers to content delivery networks and cloud platforms.  When
   usage changes, what is needed is often merely different services,
   perhaps some re-allocation reallocation of resources, resources as well as consequent
   application and continuation of existing security defences, defenses, but not
   fundamental technology or hardware changes.

   On the other hand, this is not to say that no improvements are
   needed:

   *  We need a better understanding of the health of the Internet.
      Going forward, the critical nature that the Internet plays in our
      lives means that the health of the Internet needs to receive
      significant attention.  Understanding how well networks work is
      not just a technical matter, matter; it is also of crucial importance to
      the people and economy economies of the societies using it.  Projects and
      research that monitor Internet and services performance in on a broad
      scale and across different networks are therefore important.

   *  We need to maintain defensive mechanisms to be used in times of
      crisis.  Malicious cyber actors are continually adjusting their
      tactics to take advantage of new situations, and the COVID-19
      pandemic is no exception.  Malicious actors used the high strong
      appetite for COVID-19 related COVID-19-related information as an opportunity to
      deliver malware and ransomware, 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 Indicators of Compromise (IoC) was a vital part of the
      response to COVID-19 related COVID-19-related scams and attacks.

   *  We need to ensure that broadband is available to all, 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, crisis and has further highlighted the importance of
      equitable Internet access.

   *  We need to continue to work on all the other improvements that are
      seen as necessary anyway, such as further improvements in
      security, the ability for networks and applications to collaborate
      better, etc.

   *  We need to ensure that informal collaboration between different
      parties involved in the operation of the network continues and is
      strengthened,
      strengthened to ensure continued operational resilience.

4.  Feedback on Meeting Format

   While there are frequently virtual participants in IAB workshops, the
   IAB had no experience running workshops entirely virtually.

   Feedback on this event format was largely positive, however.  It was
   particularly useful that as the three sessions were scheduled on
   Monday, Wednesday, and Friday, the time in between the sessions could
   be used for mailing list discussion and compilation of additional
   workshop material.  The positive feedback was likely at least partly
   due to the fact that many of the workshop participants knew one
   another from previous face-to-face events (primarily IETF meetings).

   The process for sending invitations to the workshop should be
   improved for next time, however, as a few invitations were initially
   lost, and in
   lost.  In a virtual meeting meeting, it may be more reasonable to invite not
   just one person but all co-authors coauthors of a paper, for instance.  At least
   for this workshop, we did not appear to suffer from having too many
   participants, and in many cases 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:

   *  Afxanasyev,  Afanasyev, A., Wang, L., Yeh, E., Zhang, B., and Zhang, L.:
      Identifying the Disease from the Symptoms: Lessons for Networking
      in the COVID-19 Era [Afxanasyev2020]

   *  Arkko, Jari: J.: Observations on Network User Behaviour During COVID-19
      [Arkko2020]

   *  Bronzino, F., Culley, E., Feamster, N.  Liu. N., Liu, S., Livingood. Livingood, J.,
      and Schmitt, P.: IAB COVID-19 Workshop: Interconnection Changes in
      the United States [Bronzino2020]

   *  Campling, Andrew A. and Lazanski, Dominique: D.: Will the Internet Still Be
      Resilient During the Next Black Swan Event?  [Campling2020]

   *  Cho, Kenjiro: K.: On the COVID-19 Impact to broadband traffic in Japan
      [Cho2020]

   *  Clark, D.: Measurement of congestion on ISP interconnection links
      [Clark2020]

   *  Favale, T., Soro, F., Trevisan, M., Drago, I., and Mellia, M.:
      Campus traffic and e-Learning during COVID-19 pandemic
      [Favale2020]

   *  Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese, I.,
      Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador, J., Vallina-
      Rodriguez, N., Hohlfeld, O., and Smaragdakis, G.: A view of
      Internet Traffic Shifts at ISP and IXPs during the COVID-19
      Pandemic [Feldmann2020]

   *  Fontugne, R., Shah, A., and Cho, K.: The Impact of COVID-19 on
      Last-mile Latency [Fontugne2020]

   *  Gillmor, D.: Vaccines, Privacy, Software Updates, and Trust
      [Gillmor2020]

   *  Gu, Y. and Li, Z. 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, R., and claffy, kc: Measuring the impact of COVID-19 on cloud
      network performance [Mok2020]

   *  Kirsty P:  Paine, K.: IAB COVID-19 Network Impacts [Kirsty2020]

6.  Workshop participants  Program Committee

   The following is an alphabetical list of participants in the
   workshop.

   * workshop program committee members were 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)

   * Arkko, 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)

   *
   Farrell, Cullen Jennings (Cisco/IAB)

   * Jennings, Colin Perkins, Ben Campbell, and Mirja Kuhlewind (Ericsson/IAB)

   *  Franziska Lichtblau (Max Planck Institute for Informatics)

   *  Dominique Lazanski
   *  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)
   *  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.  Informative References

   [Afxanasyev2020]
              Afxanasyev, A., Wang, L., Yeh, E., Zhang, B., and L.
              Zhang, "Identifying the Disease from the Symptoms: Lessons
   Kühlewind.

7.  Informative References

   [Afxanasyev2020]
              Afanasyev, A., Wang, L., Yeh, E., Zhang, B., and L. Zhang,
              "Identifying the Disease from the Symptoms: Lessons for
              Networking in the COVID-19 Era", https://www.iab.org/
              wp-content/IAB-uploads/2020/12/IAB-COVID-
              19-WS_102820.pdf , October 2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/12/IAB-
              COVID-19-WS_102820.pdf>.

   [Arkko2020]
              Arkko, J., "Observations on Network User Behaviour During
              COVID-19", https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-arkko.pdf , October 2020. 2020, <https://www.iab.org/wp-content/
              IAB-uploads/2020/10/covid19-arkko.pdf>.

   [Bronzino2020]
              Bronzino, F., Culley, E., Feamster, N., Liu, S.,
              Livingood, J., and P. Schmitt, "IAB COVID-19 Workshop:
              Interconnection Changes in the United States",
              https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-feamster.pdf , Work in
              Progress, Internet-Draft, draft-feamster-livingood-iab-
              covid19-workshop-01, 28 October 2020. 2020,
              <https://datatracker.ietf.org/doc/html/draft-feamster-
              livingood-iab-covid19-workshop-01>.

   [Campling2020]
              Campling, A. and D. Lazanski, "Will the Internet Still Be
              Resilient During the Next Black Swan Event?",
              https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-campling.pdf , October 2020.
              2020, <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-campling.pdf>.

   [Cho2020]  Cho, K., "On the COVID-19 Impact to broadband traffic in
              Japan", https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-cho.pdf , October 2020. 2020, <https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-cho.pdf>.

   [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. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-clark.pdf>.

   [Comcast2020]
              Comcast, ., "COVID-19 Network Update",
              https://corporate.comcast.com/covid-19/network/may-20-2020
              , May 2020. 2020,
              <https://corporate.comcast.com/covid-19/network/may-
              20-2020>.

   [ConsumerlabReport2020]
              Ericsson Consumer & IndustryLab, ., "Keeping ConsumerLab, "Connectivity in a COVID-19 world:
              Keeping consumers connected in a COVID-19 context",
              https://www.ericsson.com/en/reports-and- global crisis",
              <https://www.ericsson.com/en/reports-and-
              papers/consumerlab/reports/keeping-consumers-connected-
              during-the-covid-19-crisis , June 2020.
              during-the-covid-19-crisis>.

   [Favale2020]
              Favale, T., Soro, F., Trevisan, M., Drago, I., and M.
              Mellia, "Campus traffic and e-Learning during COVID-19
              pandemic", https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-favale.pdf , DOI 10.1016/j.comnet.2020.107290, October 2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-favale.pdf>.

   [Feldmann2020]
              Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese,
              I., Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador,
              J., N Vallina-Rodriguez, ., N., 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. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-feldmann.pdf>.

   [Fontugne2020]
              Fontugne, R., Shah, A., and K. Cho, "The Impact of
              COVID-19 on Last-mile Latency", https://www.iab.org/wp-
              content/IAB-uploads/2020/10/covid19-fontugne.pdf , October
              2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-fontugne.pdf>.

   [Fontugne2020-1]
              Fontugne, R., Shah, A., and K. Cho, "Persistent Last-mile
              Congestion: Not so Uncommon", Proceedings of the ACM
              Internet Measurement Conference (IMC '20) , '20),
              DOI 10.1145/3419394.3423648, October 2020. 2020,
              <https://doi.org/10.1145/3419394.3423648>.

   [Gillmor2020]
              Gillmor, D., "Vaccines, Privacy, Software Updates, and
              Trust", https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-gillmor.pdf , October 2020. 2020, <https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-gillmor.pdf>.

   [Gu2020]   Gu, Y. and Z. Li, "Covid 19 Impact on China ISP's Network
              Traffic Pattern and Solution Discussion",
              https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-gu.pdf , October 2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-gu.pdf>.

   [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. 2020, <https://www.iab.org/wp-content/IAB-
              uploads/2020/10/covid19-jennings.pdf>.

   [Kirsty2020]
              Kirsty P, .,
              Paine, K., "IAB COVID-19 Network Impacts",
              https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-kirstyp.pdf , October 2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-kirstyp.pdf>.

   [Lutu2020] Lutu, A., Perino, D., Bagnulo, M., Frias-Martinez, E., and
              J. Khangosstar, "A Characterization of the COVID-19
              Pandemic Impact on a Mobile Network Operator Traffic",
              https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-lutu.pdf ,
              DOI 10.1145/3419394.3423655, October 2020. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-lutu.pdf>.

   [McKinsey2020]
              Boland, B., De Smet, A., Palter, R., and A. Sanghvi,
              "Reimagining the office and work life after COVID-19", 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. 2020, <https://www.mckinsey.com/~/media/McKinsey/Busi
              ness%20Functions/Organization/Our%20Insights/Reimagining%2
              0the%20office%20and%20work%20life%20after%20COVID%2019/
              Reimagining-the-office-and-work-life-after-COVID-
              19-final.pdf>.

   [Mok2020]  Mok, R. and . kc 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. 2020,
              <https://www.iab.org/wp-content/IAB-uploads/2020/10/
              covid19-mok.pdf>.

   [NCTA2020] NCTA, ., "COVID-19: How Cable's Internet Networks Are
              Performing: Metrics, Trends & Observations",
              https://www.ncta.com/COVIDdashboard , 2020.
              <https://www.ncta.com/COVIDdashboard>.

   [Vodafone2020]
              Vodafone, ., "An update on Vodafone's networks",
              https://www.vodafone.com/covid19/news/update-on-vodafone-
              networks , April 2020. 2020,
              <https://www.vodafone.com/covid19/news/update-on-vodafone-
              networks>.

   [WorkplaceAnalytics2020]
              Lister, K., "Work-At-Home "Work-at-Home After Covid-19—Our Covid-19--Our Forecast",
              https://globalworkplaceanalytics.com/work-at-home-after-
              covid-19-our-forecast , 2020.
              March 2020, <https://globalworkplaceanalytics.com/work-at-
              home-after-covid-19-our-forecast>.

Appendix A.  Workshop Participants

   The following is an alphabetical list of participants in the
   workshop.

   *  Jari Arkko (Ericsson/IAB)

   *  Ben Campbell (Independent/IAB)

   *  Andrew Campling (419 Consulting)

   *  Kenjiro Cho (IIJ)

   *  kc claffy (CAIDA)

   *  David Clark (MIT CSAIL)

   *  Chris Dietzel (DE-CIX)

   *  Idilio Drago (University of Turin)

   *  Stephen Farrell (Trinity College Dublin/IAB)

   *  Nick Feamster (University of Chicago)

   *  Anja Feldmann (Max Planck Institute for Informatics)

   *  Romain Fontugne (IIJ Research Lab)

   *  Oliver Gasser (Max Planck Institute for Informatics)

   *  Daniel Kahn Gillmor (ACLU)

   *  Yunan Gu (Huawei)

   *  Oliver Hohlfeld (Brandenburg University of Technology (BTU))

   *  Jana Iyengar (Fastly)

   *  Cullen Jennings (Cisco/IAB)

   *  Mirja Kühlewind (Ericsson/IAB)

   *  Dominique Lazanski

   *  Zhenbin Li (Huawei/IAB)

   *  Franziska Lichtblau (Max Planck Institute for Informatics)

   *  Jason Livingood (Comcast)

   *  Andra Lutu (Telefonica Research)

   *  Vesna Manojlovic (RIPE NCC)

   *  Rüdiger Martin (EC)

   *  Larry Masinter (Retired)

   *  Matt Matthis (Google)

   *  Jared Mauch (Akamai/IAB)

   *  Deep Medhi (NSF)

   *  Marco Mellia (Politecnico di Torino)

   *  Ricky Mok (CAIDA)

   *  Karen O'Donoghue (Internet Society)

   *  Kirsty Paine (NCSC)

   *  Diego Perino (Telefonica Research)

   *  Colin Perkins (University of Glasgow/IRTF/IAB)

   *  Enric Pujol (Benocs)

   *  Anant Shah (Verizon Media Platform)

   *  Francesca Soro (Politecnico di Torino)

   *  Brian Trammell (Google)

   *  Martino Trevisan

   *  Georgios Tselentis (European Commission)

   *  Lan Wang (University of Memphis)

   *  Rob Wilton (Cisco)

   *  Jiankang Yao (CNNIC)

   *  Lixia Zhang (UCLA)

IAB Members at the Time of Approval

   Internet Architecture Board members at the time this document was
   approved for publication were:

      Jari Arkko
      Deborah Brungard
      Ben Campbell
      Lars Eggert
      Wes Hardaker
      Cullen Jennings
      Mirja Kühlewind
      Zhenbin Li
      Jared Mauch
      Tommy Pauly
      David Schinazi
      Russ White
      Jiankang Yao

Acknowledgments

   The authors would like to thank the workshop participants, the
   members of the IAB, the program committee, the participants in the
   architecture discussion list for the interesting discussions, and
   Cindy Morgan for the practical arrangements.

   Further special thanks to those participants who also contributed to
   this report: Romain Fontugne provided text based on his blog post at
   https://eng-blog.iij.ad.jp/archives/7722;
   <https://eng-blog.iij.ad.jp/archives/7722>; Ricky Mok for text on
   cloud
   platform; platforms; Martino Trevisan for text on campus networks; David
   Clark on congestion measurements at interconnects; Oliver Hohlfeld
   for the text on traffic growth, changes in traffic shifts, campus
   networks, and interconnections; Andra Lutu on mobile networks; and
   Kirsty Paine for text on security impacts; and thanks impacts.  Thanks to Jason Livingood
   for his review and additions.

Authors' Addresses

   Jari Arkko
   Ericsson

   Email: jari.arkko@ericsson.com

   Stephen Farrell
   Trinity College Dublin

   Email: stephen.farrell@cs.tcd.ie

   Mirja Kühlewind
   Ericsson

   Email: mirja.kuehlewind@ericsson.com

   Colin Perkins
   University of Glasgow

   Email: csp@csperkins.org