Internet Architecture Board (IAB)                               J. Arkko
Request for Comments: 9075                                    S. Farrell
Category: Informational                                     M. Kühlewind
ISSN: 2070-1721                                               C. Perkins
                                                               July 2021

Report from the IAB COVID-19 Network Impacts Workshop 2020

IAB Covid-19ネットワークからの報告Workshop 2020



The Coronavirus disease (COVID-19) pandemic caused changes in Internet user behavior, particularly during the introduction of initial quarantine and work-from-home arrangements. These behavior changes drove changes in Internet traffic.


The Internet Architecture Board (IAB) held a workshop to discuss network impacts of the pandemic on November 9-13, 2020. The workshop was held to convene interested researchers, network operators, network management experts, and Internet technologists to share their experiences. The meeting was held online given the ongoing travel and contact restrictions at that time.


Note that this document is a report on the proceedings of the workshop. The views and positions documented in this report are those of the workshop participants and do not necessarily reflect IAB views and positions.


Status of This Memo


This document is not an Internet Standards Track specification; it is published for informational purposes.


This document is a product of the Internet Architecture Board (IAB) and represents information that the IAB has deemed valuable to provide for permanent record. It represents the consensus of the Internet Architecture Board (IAB). Documents approved for publication by the IAB are not candidates for any level of Internet Standard; see Section 2 of RFC 7841.

この文書はインターネットアーキテクチャボード(IAB)の製品であり、IABが恒久的な記録を提供するのに価値があると見なされる情報を表しています。インターネットアーキテクチャボード(IAB)のコンセンサスを表します。IABによる出版の承認済みの文書は、インターネット規格のレベルの候補者ではありません。RFC 7841のセクション2を参照してください。

Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at


Copyright Notice


Copyright (c) 2021 IETF Trust and the persons identified as the document authors. All rights reserved.

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この文書は、この文書の公開日に有効なIETF文書(に関するBCP 78とIETF信頼の法的規定を受けています。この文書に関してあなたの権利と制限を説明するので、これらの文書を慎重に見直してください。

Table of Contents


   1.  Introduction
   2.  Scope
   3.  Workshop Topics and Discussion
     3.1.  Measurement-Based Observations on Network Traffic Dynamics
       3.1.1.  Overall Traffic Growth
       3.1.2.  Changes in Application Use
       3.1.3.  Mobile Networks and Mobility
       3.1.4.  A Deeper Look at Interconnections
       3.1.5.  Cloud Platforms
       3.1.6.  Last-Mile Congestion
       3.1.7.  User Behavior
     3.2.  Operational Practices and Architectural Considerations
       3.2.1.  Digital Divide
       3.2.2.  Applications
       3.2.3.  Observability
       3.2.4.  Security
       3.2.5.  Discussion
     3.3.  Conclusions
   4.  Feedback on Meeting Format
   5.  Position Papers
   6.  Program Committee
   7.  Informative References
   Appendix A.  Workshop Participants
   IAB Members at the Time of Approval
   Authors' Addresses
1. Introduction
1. はじめに

The Internet Architecture Board (IAB) held a workshop to discuss network impacts of the COVID-19 pandemic on November 9-13, 2020. The workshop was held to convene interested researchers, network operators, network management experts, and Internet technologists to share their experiences. The meeting was held online given the ongoing travel and contact restrictions at that time.

インターネット建築委員会(IAB)は、2020年11月9-13日のCovid-19 Pandemのネットワークへの影響について話し合うためにワークショップを開催しました。経験その時点で継続的な旅行と連絡先制限を考えると、会議はオンラインで開催されました。

COVID-19 has caused changes in user behavior, which in turn drove changes in Internet traffic. These changes in user behavior appeared rather abruptly and were significant, in particular during the introduction of initial quarantine and work-from-home arrangements. This caused changes in Internet traffic in terms of volume and location, as well as shifts in the types of applications used. This shift in traffic and user behavior also created a shift in security practices as well as attack patterns that made use of the attack surface, resulting from the shift to working from home in a global crisis.


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


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


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


2. Scope
2. 範囲

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

Covid-19 Pandemicは、人々の生活や世界中の社会や経済に大きな影響を与えました。しかし、それはネットワーキングに大きな影響を与えました。家庭から働いている、またはその他の方法では、日常生活のためのネットワークに依存して多数の人々が急増しました。インターネットサービスプロバイダーと事業者は、数週間に20%以上の交通伸びを報告しています。インターネット交換ポイント(IXPS)でのトラフィックは、上昇についても同様です。ほとんどの形式のネットワークトラフィックは、会話型マルチメディアトラフィックが成長し、場合によっては200%以上増加しました。会議サービスに費やされたユーザーの時間は、会議プラットフォームの一種の桁違いに上がっています。

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


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


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


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


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

* トラフィックの変更、ユーザーエクスペリエンス、および問題、サービスパフォーマンス、およびその他の関連側面の測定

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

* シーンの後ろのネットワーク管理と拡張活動に関する議論

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

* 一般的なインターネット接続、会議、メディア/エンターテイメント、およびインターネットインフラストラクチャの分野における経験の共有

* lessons learned on preparedness and operations

* 練習や業務について学んだ教訓

* lessons learned on Internet technology and architecture

* インターネット技術と建築について学んだ教訓

3. Workshop Topics and Discussion
3. ワークショップトピックと討議
3.1. Measurement-Based Observations on Network Traffic Dynamics
3.1. ネットワークトラフィックダイナミクスに関する測定ベースの観測

The workshop started with a focus on measurements. A large portion of the submitted papers presented and discussed measurement data, and these submissions provided a good basis for a better understanding of the situation, covering different angles and aspects of network traffic and different kinds of networks.


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

Covid-19 Pandemicによるインターネットトラフィックの変更はさまざまな方法でさまざまなネットワークに影響を与えます。それでも、すべてのネットワークは、トラフィックの削減、トラフィックの増加、勤務日の変更、週末の日行パターンの変更、またはトラフィッククラスの変更を見ました。交通量、指向性比、およびトラフィックの起源および宛先は、Covid-19以前とは根本的に異なりました。

At a high level, while traffic from home networks increased significantly, for the traffic in mobile networks different trends were observed. Either the traffic increased as well -- for instance, in locations where use of residential ISP services is less common -- traffic decreased as a result of reduced population mobility. This observed traffic decrease in mobile networks reflected rather the opposite trend than what was observed in residential ISPs.


While diurnal congestion at interconnect points as well in certain last-mile networks was reported, mainly in March, no persistent congestion was observed. Further, a downward trend in download throughput to certain cloud regions was measured, which can probably be explained by the increased use of cloud services. This gives another indication that the scaling of shared resources in the Internet is working reasonably well enough to handle even larger changes in traffic as experienced during the first nearly global lockdown of the COVID-19 pandemic.

マーチでは、主に3月に、ある最後のマイルのネットワークでの相互接続点での日周渋滞が報告されていますが、持続的な輻輳は観察されませんでした。さらに、特定のクラウド領域へのダウンロードスループットの下降傾向を測定した。これはおそらくクラウドサービスの使用の増加によって説明されることができる。これにより、インターネット内の共有リソースのスケーリングが、Covid-19 Pandemの最初のほぼグローバルなロックダウン中に経験されたトラフィックのより大きな変化を処理するのに十分に正しく機能しているという別の指標を示しています。

3.1.1. Overall Traffic Growth
3.1.1. 全体的なトラフィックの成長

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

世界的なパンデミックは世界中のデータトラフィックの成長を大幅に加速しました。 1つのISP、3つのIXPS、メトロポリタン教育ネットワーク、およびモバイルオペレータの測定データに基づいて、ワークショップの初めに観察されました[FeldMann2020]それは全体的に、ネットワークは重要にもかかわらず状況をよく処理することができました。そして4月の交通伸び率の急増。つまり、ロックダウンが3月に実施された後、ISPと3つのIXPSでは15~20%のトラフィックの増加が見られました。この交通の成長は、通常は1年間にわたって発生するでしょう、数週間にわたって起こりました - 実質的な増加。データスループットの観点から世界最大のインターネット交換ポイントであるDe-Cix Frankfurtで、2020年は1995年にIXPが設立されてから1年以内にピークトラフィックが最大の増加しました。さらに、モバイルトラフィックはわずかに後退しました。アクセスネットワークでは、上流のトラフィックの成長率もまた、ビデオ会議やその他のリモート作業や学校のアプリケーションの採用と使用の増大を反映して、下流のトラフィックの成長を上回りました。

Most traffic increases happened outside of pre-pandemic peak hours. Before the first COVID-19 lockdowns, the main time of use was in the evening hours during the week, whereas, since March, it has been spread more equally across the day. That is, the increase in usage has mainly occurred outside the previous peak usage times (e.g., during the day while working from home). This means that, for the first time, network utilization on weekdays resembled that on weekends. The effects of the increased traffic volume could easily be absorbed, either by using existing reserve capacity or by quickly switching additional bandwidth. This is one reason why the Internet was able to cope well with the pandemic during the first lockdown period.


Some of the lockdowns were lifted or relaxed around May 2020. As people were allowed to resume some of their daily activities outside of their home again, as expected, there was a decrease in the traffic observed at the IXPs and the ISP; instead, mobile traffic began to grow again.


3.1.2. Changes in Application Use
3.1.2. アプリケーションの使用の変更

The composition of data traffic has changed since the beginning of the pandemic: the use of videoconferencing services and virtual private networks (VPNs) for access to company resources from the home environment has risen sharply. In ISP and IXP networks, it was observed [Feldmann2020] that traffic associated with web conferencing, video, and gaming increased significantly in March 2020 as a result of the increasing user demand for solutions like Zoom or Microsoft Teams. For example, the relative traffic share of many "essential" applications like VPN and conferencing tools increased by more than 200%.


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

また、人々が自宅でもっと時間を費やしたように、彼らはビデオを見ることやゲームをプレイする傾向があり、娯楽の交通需要が増えています。同時に、他のトラフィッククラスのトラフィックシェアは、実質的に、例えば、教育、ソーシャルメディア、およびいくつかの期間のために、コンテンツ配信ネットワーク(CDNS)について実質的に減少しました。4月と6月には、Web会議のトラフィックはまだ飛行中のシナリオと比較して高く、CDNやソーシャルメディアトラフィックのわずかな減少が観察されました。この月の間に、多くの人々がまだ家から働いていましたが、制限は持ち上げられたり、リラックスしたりしていました。これにより、人内の社会活動の増加とオンライン社会活動の減少がありました。 Example Campus Networks キャンパスネットワークの例

Changes in traffic have been observed at university campus networks as well, especially due to the necessary adoption of remote teaching. The Politecnico di Torino (Italy) deployed its in-house solution for remote teaching, which caused the outgoing traffic to grow by 2.5 times, driven by more than 600 daily online classes. Incoming traffic instead decreased by a factor of 10 due to the cessation of any in-person activity. Based on their measurements, this change in traffic and network usage did not, however, lead to noticeable performance impairments, nor has significantly poor performance been observed in students in remote regions of Italy. Outgoing traffic also increased due to other remote working solutions, such as collaboration platforms, VPNs, and remote desktops.

特にリモート教育の必要な採用により、大学のキャンパスネットワークでも交通量の変化が見られました。Politecnico di Torino(イタリア)は、遠隔教育のために社内ソリューションを展開しました。着信トラフィックは代わりに、個人内の活動の停止のために10倍減少しました。測定に基づいて、この交通量の変化やネットワークの使用法は、顕著なパフォーマンスの障害をもたらし、イタリアの遠隔地域の学生には顕著なパフォーマンスが著しく低下していませんでした。発信トラフィックは、コラボレーションプラットフォーム、VPN、およびリモートデスクトップなど、他のリモートワーキングソリューションのために増加しました。

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

Madridの首都圏に16個の独立した大学と研究センターを結ぶヨーロッパの教育研究ネットワーク、RediMadrid [Feldmann2020]を測定することによって同様の変更が観察されました。流行中の勤務日の交通量で最大55%の低下が観察された。ISP / IXPネットワークの調査結果と同様に、勤務日と週末の日数が総トラフィックの点でより類似していることが観察されました。毎時交通パターンは、午後9時から午前7時の間の交通量の増加を明らかにしています。これは、ユーザーが珍しい時に頻繁に取り組んでいる可能性がありますが、大学のネットワークリソースにアクセスしたところでは、海外の学生(主にラテンアメリカや東アジアからの主にラテンアメリカや東アジアからのもの)が原因である可能性があります。彼らの母国から。

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


3.1.3. Mobile Networks and Mobility
3.1.3. モバイルネットワークとモビリティ

Mobile network data usage appeared to decline following the imposition of localized lockdown measures as these reduced typical levels of mobility and roaming.


[Lutu2020] measured the cellular network of O2 UK to evaluate how the changes in people's mobility impacted traffic patterns. By analyzing cellular network signaling information regarding users' device mobility activity, they observed a decrease of 50% in mobility (according to different mobility metrics) in the UK during the lockdown period. As they found no correlation between this reduction in mobility and the number of confirmed COVID-19 cases, only the enforced government order was effective in significantly reducing mobility, and this reduction was more significant in densely populated urban areas than in rural areas. For London specifically, it could be observed from the mobile network data that approximately 10% of residents temporarily relocated during the lockdown.


These mobility changes had immediate implications in the traffic patterns of the cellular network. The downlink data traffic volume aggregated for all bearers (including conversational voice) decreased for the entire UK by up to 25% during the lockdown period. This correlates with the reduction in mobility that was observed countrywide, which likely resulted in people relying more on residential broadband Internet access to run download-intensive applications such as video streaming. The observed decrease in the radio cell load, with a reduction of approximately 15% across the UK after the stay-at-home order was enacted, further corroborates the drop in cellular connectivity usage.


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


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


3.1.4. A Deeper Look at Interconnections
3.1.4. 相互接続を深く見てください

Traffic at points of network interconnection noticeably increased, but most operators reacted quickly by rapidly adding additional capacity [Feldmann2020]. The amount of increase varied, with some networks that hosted popular applications such as videoconferencing experiencing traffic growth of several hundred to several thousand percent. At the IXP level, it was observed that port utilization increased. This phenomenon is mostly explained by higher traffic demand from residential users.


Measurements of interconnection links at major US ISPs by the Center for Applied Internet Data Analysis (CAIDA) and the Massachusetts Institute of Technology (MIT) found some evidence of diurnal congestion around the March 2020 time frame [Clark2020], but most of this congestion disappeared in a few weeks, which suggests that operators indeed took steps to add capacity or otherwise mitigate the congestion.


3.1.5. Cloud Platforms
3.1.5. クラウドプラットフォーム

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

Cloud Infrastructureは、Covid-19 Pandemの間に社会的な距離を実践するための帯域幅集約型のビデオ会議および遠隔学習ツールをサポートする上で重要な役割を果たしました。クラウドプラットフォームとアクセスネットワーク間のネットワーク輻輳は、これらのクラウドベースのアプリケーションの経験の質に影響を与える可能性があります。Caida Leveraged Webベースのスピードテストサーバーは、パブリッククラウドプラットフォーム内の仮想マシンからのスループット測定を米国のさまざまなアクセスISPにダウンロードしてアップロードしてアップロードします[MOK2020]。

The key findings included the following:


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

* 永続的な輻輳イベントは、クラウドプラットフォームとこれらのネットワーク間で広く観察されていませんでした。

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

* 米国の郊外の地域を提供する地域ISPへの出口方向への持続的輻輳の証拠がありました。彼らのユーザーは、クラウドからの貧弱なビデオストリーミングまたはファイルのダウンロードパフォーマンスを患っていた可能性があります。

* The macroscopic analysis over 3 months (June-August 2020) revealed downward trends in download throughput from ISPs and educational networks to certain cloud regions. We believe that increased use of the cloud in the pandemic could be one of the factors that contributed to the decreased performance.

* 3ヶ月間の巨視的分析(2020年6月-8月)は、ISPおよび教育ネットワークから特定のクラウド地域へのダウンロードのスループットの下方傾向を明らかにしました。パンデミックにおける雲の使用の増加は、パフォーマンスの低下に貢献した要因の1つである可能性があると考えています。

3.1.6. Last-Mile Congestion
3.1.6. 最後のマイルの輻輳

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

最後のマイルはブロードバンド接続性の中心的なものであり、最後のマイルの性能は一般的に低い経験の質に変換されます。最近のインターネット測定会議(IMC '20)研究論文、Fontugne et al。 646 ASESにあるATLASプローブからのReseaux IP Europeens(RIPE)のATLASプローブからのTracerouteデータを使用し、再発性能劣化を探しています[Fontugne 2020-1]。彼らは、通常の時代にATLASプローブがASESの10%での持続的な最後のマイルの輻輳を経験することを見出したが、彼らはCoviD - 19の発生中に55%の混雑したASを記録した。在宅滞在対策によって引き起こされるこの劣化は、非常に多数のユーザーと世界の特定の地域でネットワークで特にマークされています。彼らは、日本電信および電話(NTT)株式会社を具体的に見て、日本電信電話(NTT)社内で最も影響を受けた国であることを日本が発見しましたが、インターネットイニシアチブジャパンを含むいくつかの日本のネットワークについて同様の観察に注意してください(AS2497) 。

From mid-2020 onward, however, they observed better performance than before the pandemic. In Japan, this was partly due to the deployments originally planned for accommodating the Tokyo Olympics, and, more generally, it reflects the efforts of network operators to cope with these exceptional circumstances. The pandemic has demonstrated that its adaptive design and proficient community can keep the Internet operational during such unprecedented events. Also, from the numerous research and operational reports recently published, the pandemic is apparently shaping a more resilient Internet; as Nietzsche wrote, "What does not kill me makes me stronger".


3.1.7. User Behavior
3.1.7. ユーザーの動作

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

ユーザーが必要とするトラフィックの種類も2020年に変更されました。アップストリームトラフィックは、テレビ電話、リモートスクーリング、および類似のアプリケーションの使用により増加しました。National Cable&Telecommunications(NCTA)とComcastは、ダウンストリームトラフィックが20%増加したが、上流のトラフィックは30~37%〜[Comcast2020]に成長したと報告しました。ボーダフォンは、上流のトラフィックがいくつかの市場で100%増加したことを報告しました[Vodafone2020]。

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

Ericsson ConsumerLabは、危機の間にその使用と経験に関するユーザーを調査しました。[ConsumerLab Report 2020]の重要な調査結果の一部は次のとおりです。

* 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.

* 9人のユーザーにインターネット活動を増やしました。また、5 in 5の1つのオンライン活動を開始しました。高齢者の多くは、彼らがビデオ通話によって助けられたと感じました。両親は彼らの子供の教育が助けられたと感じました。等々。

* Network performance was, in general, found satisfactory. 6 in 10 were very satisfied with fixed broadband, and 3 in 4 felt that mobile broadband was the same or better compared to before the crisis. Consumers valued resilience and quality of service as the most important responsibility for network operators.

* ネットワークのパフォーマンスは一般的に満足のいくものでした。10の6 in 10は固定ブロードバンドに非常に満足しており、4 in 4では、モバイルブロードバンドは危機前と比較して同じかそれより良いと感じました。消費者は、ネットワーク事業者に対する最も重要な責任として回復力とサービス品質を大切にしています。

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

* スマートフォンアプリケーションの使用状況は、Covid-19の追跡と情報、遠隔作業、eラーニング、健康、教育、リモートヘルスコンサルテーション、および社会的共有体験アプリケーションに関連するアプリの最速の成長を変更しました。最大の減少は旅行や予約、乗り心地、駐車場などでした。

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

一部の行動はおそらく恒久的な変更です[ConsumerLabReport2020]。古い世代などの多くの消費者によるビデオ通話やその他の新しいサービスの採用は、長期的な効果がある可能性があります。さまざまな組織の調査は、リモートワークに興味がある人の数の長期的な増加を指摘しています[WorkPlaceAnalytics2020] [McKinSey2020]。

3.2. Operational Practices and Architectural Considerations
3.2. 運用慣行と建築に関する考慮事項

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


3.2.1. Digital Divide
3.2.1. デジタルデバイド

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


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


3.2.2. Applications
3.2.2. アプリケーション

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.

Web会議システム(例えば、Microsoft Teams、Zoom、Zoom、WebEx)は、ロックダウンなどの公共ポリシーの変更に応じて、15~20%の一晩のトラフィックの増加を伴う信じられないほどの成長をもたらしました。これはインフラプロビジョニングの重要で急激な変更を必要としました。

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


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


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


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


3.2.3. Observability
3.2.3. 観察可能

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


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


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


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

さらに、特に報告された情報をインターネット内の複数のネットワークにわたって共有する必要がある場合は、それらを修正できる人に問題報告をルーティングすることが困難であることが明らかです。Covid Enhanced Coperationは、問題をデバッグすることを容易にしました。通信行は重要です。

3.2.4. Security
3.2.4. 安全

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


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


Of all scams detected by the United Kingdom National Cyber Security Centre (UK NCSC) that purported to originate from the UK Government, more related to COVID-19 than any other subject. There are other reports of a strong rise in phishing, fraud, and scams related to COVID [Kirsty2020]. Although the overall levels of cybercrime have not increased from the data seen to date, there was certainly a shift in activity as both the NCSC and the Department of Homeland Security Cybersecurity and Infrastructure Security Agency (DHS CISA) saw growing use of COVID-19-related themes by malicious cyber actors as a lure. Attackers used COVID-19-related scams and phishing emails to target individuals, small and medium businesses, large organizations, and organizations involved in both national and international COVID-19 responses (healthcare bodies, pharmaceutical companies, academia, and medical research organizations). New targets (for example, organizations involved in COVID-19 vaccine development) were attacked using VPN exploits, highlighting the potential consequences of vulnerable infrastructure.

イギリス国立サイバーセキュリティセンター(イギリスNCSC)によって検出されたすべての詐欺のうち、英国政府から由来し、他のどの科目よりもCOVID-19に関連しています。 Covid [Kirsty2020]に関連するフィッシング、詐欺、および詐欺の強い上昇の報告がある。全体的なサイバー犯罪者のレベルは日付から日付に増加していませんが、NCSCと国土安全保障サイバーセキュリティとインフラストラクチャセキュリティエージェンシー(DHS CISA)の両方としての活動の移行がありました(DHS CISA)、Covid-19-悪意のあるサイバー俳優による関連テーマ。攻撃者は、国内および国際的なCovid-19の回答(医療機関、製薬会社、学術界、および医学研究機関)に関わる個人、中小企業、大規模な組織、および組織を対象としたCovid-19関連の詐欺およびフィッシングメールを使用しました。新しいターゲット(例えば、Covid-19ワクチン開発に関与する組織)は、VPNの悪用を使用して攻撃され、脆弱なインフラストラクチャの潜在的な影響を強調しました。

It's unclear how to effectively detect and counter these attacks at scale. Approaches such as using Indicators of Compromise and crowdsourced flagging of suspicious emails were found to be effective in response to COVID-19-related scams [Kirsty2020], and observing the DNS to detect malicious use is widespread and effective. The use of DNS over HTTPS offers privacy benefits, but current deployment models can bypass these existing protective DNS measures.

スケールでこれらの攻撃を効果的に検出してカウンターする方法は不明です。不審なEメールの妥協点とクラウドオブフラッグの指標を使用するなどのアプローチは、Covid-19関連のSCAM [Kirsty2020]に対応して有効であり、悪意のある用途を検出するためにDNSを観察することが広くて効果的です。HTTPSを介したDNSの使用はプライバシーの利点を提供しますが、現在の展開モデルはこれらの既存の保護DNSメジャーを回避できます。

It was also noted that when everyone moves to performing their job online, lack of understanding of security becomes a bigger issue. Is it reasonable to expect every user of the Internet to have password training? Or is there a fundamental problem with a technical solution? Modern advice advocates a layered approach to security defenses, with user education forming just one of those layers.


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

ズームなどの通信プラットフォームは新しいことではありません。多くの人が何年もの間それらを使用しましたが、Covid-19として、これらの技術に向かって団体や個人が増えていることを見ました。順番に、パスワードで保護されていない、または攻撃ベクトルとしての非パッチソフトウェアを活用したHijacking Online Meetingsを通じて悪意のあるサイバーアクターの活動が増加しました。新規または既存の対策は、次の脆弱なサービスに対して課税された攻撃からユーザーを保護することができますか?

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


3.2.5. Discussion
3.2.5. 考察

There is a concern that we're missing observability for the network as a whole. Each application provider and operator has their own little lens. No one has the big-picture view of the network.


How much of a safety margin do we need? Some of the resiliency comes from us not running the network too close to its limit. This allows traffic to shift and gives headroom for the network to cope. The best-effort nature of the network may help here. Using techniques to run the network closer to its limits usually improves performance, but highly optimized networks may be less robust.


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


3.3. Conclusions
3.3. 結論

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


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


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


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

一般に、インターネットはまた、少なくともいくつかの範囲内で、新しい状況に適応するのに適しています。インターネットは、今日の特定のトラフィックタイプのために最適化されるのではなく、柔軟性と拡張性のために設計されています。これにより、多くのアプリケーションや多くの展開状況で使用し、必要に応じて変更を加えることができます。一般性がシステム全体の多くの部分に、Basic Internet Technology、ブラウザ、ネームサーバーからコンテンツ配信ネットワーク、クラウドプラットフォームへのものです。使用法が変更された場合、必要とされているのは、単にさまざまなサービス、おそらくその結果、既存のセキュリティ防御の継続、および根本的なテクノロジやハードウェアの変更ではありません。

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


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

* インターネットの健康をよりよく理解する必要があります。今後も、インターネットが私たちの命に就く重要な性質は、インターネットの健康が大きな注意を払う必要があることを意味します。ネットワークがどの程度働くかを理解することは単なる技術的な問題ではありません。それを使用して社会の人々や経済にとって重要な重要性もあります。そのため、インターネットとサービスのパフォーマンスを広いスケールで監視するプロジェクトと研究が重要です。

* We need to maintain defensive mechanisms to be used in times of crisis. Malicious cyber actors are continually adjusting their tactics to take advantage of new situations, and the COVID-19 pandemic is no exception. Malicious actors used the strong appetite for COVID-19-related information as an opportunity to deliver malware and ransomware and to steal user credentials. Against the landscape of a shift to working from home and an increase in users vulnerable to attack, and as IT departments were often overwhelmed by rolling out new infrastructure and devices, sharing Indicators of Compromise (IoC) was a vital part of the response to COVID-19-related scams and attacks.

* 危機時に使用される防御メカニズムを維持する必要があります。悪意のあるサイバー俳優は、新しい状況を利用するために戦術を継続的に調整し、Covid-19 Pandemは例外ではありません。悪意のある俳優は、MalwareとRansomwareを配信し、ユーザーの資格情報を盗む機会として、Covid-19関連情報のために強い食欲を使用しました。家庭からの働きや攻撃に脆弱なユーザーの増加のためのシフトの風景に対して、そしてIT部門が新しいインフラとデバイスを転がして過剰に影響を与えたので、妥協の指標(IOC)の共有指標は、Covidへの対応の重要な部分でした。-19関連の詐欺と攻撃。

* We need to ensure that broadband is available to all and that Internet services equally serve different groups. The pandemic has shown how the effects of the digital divide can be amplified during a crisis and has further highlighted the importance of equitable Internet access.

* ブロードバンドがすべてのもので利用可能であり、インターネットサービスが異なるグループに均等に役立つようにする必要があります。パンデミックは、デジタルデバイドの影響を危機の間に増幅することができる方法を示しており、公平なインターネットアクセスの重要性をさらに強調しています。

* 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.

* 安全性のさらなる改善、ネットワークやアプリケーションがより良くなっているなど、必要に応じて見られた他のすべての改善に取り組む必要があります。

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

* ネットワークの操作に関わる異なる関係者間の非公式のコラボレーションが続くことを確実にし、継続的な運営復興を確実にするために強化されています。

4. Feedback on Meeting Format
4. 会議形式に関するフィードバック

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


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


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


5. Position Papers
5. ポジションペーパー

The following position papers were received, in alphabetical order:


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

* AFANASASYEV、A.、Wang、L.、Yeh、E.、Zhang、B.、およびZhang、L。:症状からの疾患の特定:Covid-19時代のネットワーキングのためのレッスン[AFXANASYEV2020]

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

* arkko、j .: Covid-19のネットワークユーザーの行動に関する観測[ARKKO2020]

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

* Bronzino、F.、Culley、E.、Feamster、N.、N.、Liu、S.、Livingood、J.、およびSchmitt、P。:IAB Covid-19ワークショップ:アメリカ合衆国の相互接続の変化[Bronzino2020]

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

* カンピング、A。およびラザンスキ、D。[カンプリング2020]

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

* cho、k。:日本のブロードバンドトラフィックへの影響[CHO 2020]

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

* クラーク、D。:ISP相互接続リンクの輻輳の測定[Clark2020]

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

* Favale、T.、Soro、F.、Trevisan、M.、Drago、I.、およびMellia、M。:COVID-19 Pandemic [Favale2020]中のキャンパス交通とeラーニング

* 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]

* Feldmann、A.、Gasser、O.、Lichtblau、F.、Pujol、E.、Peese、I.、Dietzel、C.、Wagner、D.、Wichtlhuber、M.、Tapiador、J.、Vallina-Rodriguez、N。、Hohlfeld、O.、およびSmaragdakis、G。:Covid-19 Pandemic [Feldmann2020]の間のISPおよびIXPSでのインターネット交通シフトのビュー

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

* Fontugne、R.、Shah、A.、Cho、K。:Last-Mile LatencyのCovid-19の影響

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

* Gillmor、D。:ワクチン、プライバシー、ソフトウェアアップデート、および信頼[Gillmor2020]

* Gu, Y. and Li, Z.: Covid 19 Impact on China ISP's Network Traffic Pattern and Solution Discussion [Gu2020]

* gu、y.およびli、z。:COVID 19中国ISPのネットワークトラフィックパターンとソリューションディスカッションへの影響[GU2020]

* Jennings, C. and Kozanian, P.: WebEx Scaling During Covid [Jennings2020]

* Jennings、C、Kozanian、P。:Covidの間のWebExスケーリング[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]

* ルツ、A.、Perino、D.、Bagnulo、M.、Frias-Martinez、E.、およびKhangoSSTAR、J。:モバイルネットワーク事業者トラフィックへのCovid-19のパンデミック影響の特性化[LUTU2020]

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

* MOK、R.、およびCLAFFY、KC:クラウドネットワークパフォーマンスへのCOVID-19の影響の測定[MOK2020]

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

* Paine、K。:IAB Covid-19ネットワークへの影響[Kirsty2020]

6. Program Committee
6. プログラム委員会

The workshop program committee members were Jari Arkko, Stephen Farrell, Cullen Jennings, Colin Perkins, Ben Campbell, and Mirja Kühlewind.

ワークショッププログラム委員会のメンバーは、Jari Arkko、Stephen Farrell、Cullen Jennings、Colin Perkins、Ben Campbell、MirjaKühlewindでした。

7. Informative References
7. 参考引用

[Afxanasyev2020] Afanasyev, A., Wang, L., Yeh, E., Zhang, B., and L. Zhang, "Identifying the Disease from the Symptoms: Lessons for Networking in the COVID-19 Era", October 2020, <>.

[AFXANASYEV2020] Afanasyev、A.、A.、L.、Yeh、E、E、E、Zhang、B.、L. Zhang、「症状からの疾患の特定:Covid-19時代のネットワーキングのためのレッスン」、2020年10月、<>。

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

[ARKKO2020] Arkko、J.、2020年10月、2020年10月、< iab-uploads / 2020/10 / covid19-arkko。PDF>。

[Bronzino2020] Bronzino, F., Culley, E., Feamster, N., Liu, S., Livingood, J., and P. Schmitt, "IAB COVID-19 Workshop: Interconnection Changes in the United States", Work in Progress, Internet-Draft, draft-feamster-livingood-iab-covid19-workshop-01, 28 October 2020, <>.

[Bronzino2020] Bronzino、F.、Culley、E.、Feamster、N.、Liu、S.、Livingood、J.、およびP. Schmitt、「IAB Covid-19 Workshop:アメリカ合衆国の相互接続の変化」進捗状況、インターネットドラフト、ドラフト - Feamstre-Livingood-Iab-Covid19-Workshop-01,2020、<>。

[Campling2020] Campling, A. and D. Lazanski, "Will the Internet Still Be Resilient During the Next Black Swan Event?", October 2020, < covid19-campling.pdf>.

[Campling2020]カンピング、A.およびD. Lazanski、「インターネットはまだ次の黒い白鳥のイベントの間にまだ弾力的になるの?」、2020年10月、< / Covid19-Campling.pdf>。

[Cho2020] Cho, K., "On the COVID-19 Impact to broadband traffic in Japan", October 2020, <>.

[CHO 2020] Cho、K。、「日本のブロードバンドトラフィックへの影響について」、2020年10月、<>。

[Clark2020] Clark, D., "Measurement of congestion on ISP interconnection links", October 2020, < covid19-clark.pdf>.

[Clark2020] Clark、D.、「ISPインターコネクトリンクの輻輳の測定」、2020年10月、<>。

[Comcast2020] Comcast, "COVID-19 Network Update", May 2020, <>.

[Comcast2020] Comcast、 "Covid-19 Network Update"、2020年5月、<>。

[ConsumerlabReport2020] Ericsson ConsumerLab, "Connectivity in a COVID-19 world: Keeping consumers connected in a global crisis", <>.

[ConsumerLabReport2020] Ericsson ConsumerLab、「Covid-19のコネクティビティ」、「消費者を世界の危機に接続し続ける」、< - Covid-19-Crisisの間に接続されています。

[Favale2020] Favale, T., Soro, F., Trevisan, M., Drago, I., and M. Mellia, "Campus traffic and e-Learning during COVID-19 pandemic", DOI 10.1016/j.comnet.2020.107290, October 2020, < covid19-favale.pdf>.

[Favale2020] Favale、T.、Soro、F.、Trevisan、M.、Drago、I.、およびM.Mellia、「Covid-19 Pandemicのキャンパス交通とeラーニング」、DOI 10.1016 /年10月、< covid19-favale.pdf>。

[Feldmann2020] Feldmann, A., Gasser, O., Lichtblau, F., Pujol, E., Poese, I., Dietzel, C., Wagner, D., Wichtlhuber, M., Tapiador, J., Vallina-Rodriguez, N., Hohlfeld, O., and G. Smaragdakis, "A view of Internet Traffic Shifts at ISP and IXPs during the COVID-19 Pandemic", October 2020, < covid19-feldmann.pdf>.

[Feldmann2020] Feldmann、A.、Gasser、O.、Lichtblau、F.、Pujol、E.、Poese、I.、Dietzel、C.、Wagner、D.、Wichtlhuber、M.、Tapiador、J.、Vallina-Rodriguez、N.、Hohlfeld、O.、およびG.Smaragdakis、2020年10月、2020年10月、<に登録してください。コンテンツ/ IABアップロード/ 2020/10 / COVID19-FeldMann.pdf>。

[Fontugne2020] Fontugne, R., Shah, A., and K. Cho, "The Impact of COVID-19 on Last-mile Latency", October 2020, < covid19-fontugne.pdf>.

[Fontugne2020] Fontugne、R.、Shah、A.、K.町、2020年10月、2020年10月、< / 2020/10 / Covid19-fontugne.pdf>。

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

[Fontugne2020-1] Fontugne、R.、Shah、A.、K. CHO、「持続的な最後のマイル輻輳:それほど珍しくない」、ACMインターネット測定会議(IMC '20)、DOI 10.1145 / 3419394.34236482020年10月、<>。

[Gillmor2020] Gillmor, D., "Vaccines, Privacy, Software Updates, and Trust", October 2020, <>.

[gillmor2020] Gillmor、D.、「ワクチン、プライバシー、ソフトウェアアップデート、および信頼」、2020年10月、<。PDF>。

[Gu2020] Gu, Y. and Z. Li, "Covid 19 Impact on China ISP's Network Traffic Pattern and Solution Discussion", October 2020, < covid19-gu.pdf>.

[GU2020] GU、Y.およびZ.Li、「Covid 19中国ISPのネットワークトラフィックパターンとソリューションディスカッションへの影響」、2020年10月、< 10 / covid19-gu.pdf>。

[Jennings2020] Jennings, C. and P. Kozanian, "WebEx Scaling During Covid", October 2020, <>.

[Jennings2020] Jennings、C、P.コサニア語、2020年10月、2020年10月、<>。

[Kirsty2020] Paine, K., "IAB COVID-19 Network Impacts", October 2020, < covid19-kirstyp.pdf>.

[Kirsty2020] Paine、K。、「IAB Covid-19ネットワークインパクト」、2020年10月、<>。

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

[LUTU2020]ルツ、A。、Perino、D.、Bagnulo、M.、Frias-Martinez、E.、およびJ.HhangoSSTAR、「モバイルネットワーク事業者トラフィックへのCovid-19のパンデミック影響の特性」、DOI 10.11452020年10月2020年10月、< covid19-lutu.pdf>。

[McKinsey2020] Boland, B., De Smet, A., Palter, R., and A. Sanghvi, "Reimagining the office and work life after COVID-19", June 2020, < 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>.

[MckinSey2020]ボランダ、B.、De Smet、A.、Palter、R.、およびA.Sanghvi、2020年6月、2020年6月、<の「オフィスと労働生活の再マジック化」/〜/ MACKINSEY / BUSI NESS%20関数/組織/私たちの%20 Insights / Reimagianing%2 0.%20 office%20.%20件20.20件20090TER 2000FID%200FID%-COVID-19-Final.pdf>。

[Mok2020] Mok, R. and kc. claffy, "Measuring the impact of COVID-19 on cloud network performance", October 2020, < covid19-mok.pdf>.

[MOK2020] MOK、R.およびKC。2020年10月、< covid19-mok.pdf>。

[NCTA2020] NCTA, "COVID-19: How Cable's Internet Networks Are Performing: Metrics, Trends & Observations", <>.

[NCTA2020] NCTA、「COVID-19:ケーブルのインターネットネットワークはどのようにしていますか:メトリック、トレンド&観測 "、<>。

[Vodafone2020] Vodafone, "An update on Vodafone's networks", April 2020, <>.


[WorkplaceAnalytics2020] Lister, K., "Work-at-Home After Covid-19--Our Forecast", March 2020, <>.

[WorkPlaceAnalytics2020]リスター、K。、「Covid-19 - 私たちの予測後の勤務中」、2020年3月、<予測>。

Appendix A. Workshop Participants

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


* Jari Arkko (Ericsson/IAB)

* Jari Arkko(Ericsson / Iab)

* Ben Campbell (Independent/IAB)

* ベンキャンベル(独立/ IAB)

* Andrew Campling (419 Consulting)

* Andrewカンプリング(419コンサルティング)

* Kenjiro Cho (IIJ)

* ケンジイロ町(IIJ)

* kc claffy (CAIDA)

* KC Claffy(Caida)

* David Clark (MIT CSAIL)

* David Clark(Mit Csail)

* Chris Dietzel (DE-CIX)

* クリス・ディビジェル(De-CIX)

* Idilio Drago (University of Turin)

* Idilio Drago(トリノ大学)

* Stephen Farrell (Trinity College Dublin/IAB)

* スティーブンファレル(トリニティカレッジダブリン/ IAB)

* Nick Feamster (University of Chicago)

* ニックフェームスター(シカゴ大学)

* Anja Feldmann (Max Planck Institute for Informatics)

* Anja Feldmann(マックスプランク情報学研究所)

* Romain Fontugne (IIJ Research Lab)

* ロマンフォングヌ(IIJリサーチラボ)

* Oliver Gasser (Max Planck Institute for Informatics)

* オリバーガッサー(マックスプランク情報学研究所)

* Daniel Kahn Gillmor (ACLU)

* ダニエル・カーン・ジョルコール(ACLU)

* Yunan Gu (Huawei)

* 雲山区(Huawei)

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

* Oliver Hohlfeld(Brandenburg Technology大学(BTU))

* Jana Iyengar (Fastly)

* Jana Iyengar(早く)

* Cullen Jennings (Cisco/IAB)

* Cullen Jennings(Cisco / IAB)

* Mirja Kühlewind (Ericsson/IAB)

* MirjaKühühlewind(エリクソン/ IAB)

* Dominique Lazanski

* ドミニクラザンスキー

* Zhenbin Li (Huawei/IAB)

* Zhenbin Li(Huawei / Iab)

* Franziska Lichtblau (Max Planck Institute for Informatics)

* Franziska Lichtblau(マックスプランク情報学研究所)

* Jason Livingood (Comcast)

* Jason Livingood(コムキャスト)

* Andra Lutu (Telefonica Research)

* アンドラルツ(テレフォニカリサーチ)

* Vesna Manojlovic (RIPE NCC)

* Vesna Manojlovic(熟したNCC)

* Rüdiger Martin (EC)

* RüdigerMartin(EC)

* Larry Masinter (Retired)

* ラリーマスインター(引退)

* Matt Matthis (Google)

* マットマタス(Google)

* Jared Mauch (Akamai/IAB)

* ジャレッド・マックス(Akamai / Iab)

* Deep Medhi (NSF)

* ディープメディ(NSF)

* Marco Mellia (Politecnico di Torino)

* マルコメリ(Politecnico di Torino)

* Ricky Mok (CAIDA)

* リッキーモック(カイダ)

* Karen O'Donoghue (Internet Society)

* カレン・オードノグー(インターネット社会)

* Kirsty Paine (NCSC)

* Kirsty Paine(NCSC)

* Diego Perino (Telefonica Research)

* Diego Perino(テレフォニカリサーチ)

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

* コリンパーキンズ(グラスゴー大学/ IRTF / IAB)

* Enric Pujol (Benocs)

* Enric Pujol(Benocs)

* Anant Shah (Verizon Media Platform)

* Anant Shah(Verizon Media Platform)

* Francesca Soro (Politecnico di Torino)

* Francesca Soro(Politecnico di Torino)

* Brian Trammell (Google)

* Brian Trammell(Google)

* Martino Trevisan

* Martino Trevisan

* Georgios Tselentis (European Commission)

* Georgios Tselentis(欧州委員会)

* Lan Wang (University of Memphis)

* LAN Wang(メンフィス大学)

* Rob Wilton (Cisco)

* ロブウィルトン(シスコ)

* Jiankang Yao (CNNIC)

* Jiankang Yao(CNNIC)

* Lixia Zhang (UCLA)

* 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

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



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.

著者らは、Workshopの参加者、IABのメンバー、プログラム委員会、アーキテクチャディスカッションリストの参加者、および実用的な取り決めのためのCindy Morganに感謝します。

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

このレポートにも貢献した参加者のおかげで、<>での彼のブログ投稿に基づいてテキストを提供しました。クラウドプラットフォーム上のテキストのためのRicky Mok。キャンパスネットワーク上のテキスト用のMartino Trevisan;相互接続時の輻輳測定に関するDavid Clarkトラフィックの成長、トラフィックシフト、キャンパスネットワーク、および相互接続の変化のためのテキストのOliver Hohlfeld。モバイルネットワーク上のAndra Lutu。セキュリティへの影響に関するテキストのためのKirsty Paine。彼のレビューと追加のためにJason Livingoodのおかげで。

Authors' Addresses


Jari Arkko Ericsson

Jari Arkko Ericsson.


Stephen Farrell Trinity College Dublin



Mirja Kühlewind Ericsson



Colin Perkins University of Glasgow

Colin Perkins Glasgow大学