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Article overview
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Impact of Evolving Protocols and COVID-19 on Internet Traffic Shares | | Luca Schumann
; Trinh Viet Doan
; Tanya Shreedhar
; Ricky Mok
; Vaibhav Bajpai
; | | Date: |
1 Jan 2022 | | Abstract: | The rapid deployment of new Internet protocols over the last few years and
the COVID-19 pandemic more recently (2020) has resulted in a change in the
Internet traffic composition. Consequently, an updated microscopic view of
traffic shares is needed to understand how the Internet is evolving to capture
both such shorter- and longer-term events. Toward this end, we observe traffic
composition at a research network in Japan and a Tier-1 ISP in the USA. We
analyze the traffic traces passively captured at two inter-domain links: MAWI
(Japan) and CAIDA (New York-Sao Paulo), which cover 100GB of data for MAWI
traces and 4TB of data for CAIDA traces in total. We begin by studying the
impact of COVID-19 on the MAWI link: We find a substantial increase in the
traffic volume of OpenVPN and rsync, as well as increases in traffic volume
from cloud storage and video conferencing services, which shows that clients
shift to remote work during the pandemic. For traffic traces between March 2018
to December 2018, we find that the use of IPv6 is increasing quickly on the
CAIDA monitor: The IPv6 traffic volume increases from 1.1% in March 2018 to
6.1% in December 2018, while the IPv6 traffic share remains stable in the MAWI
dataset at around 9% of the traffic volume. Among other protocols at the
application layer, 60%-70% of IPv4 traffic on the CAIDA link is HTTP(S)
traffic, out of which two-thirds are encrypted; for the MAWI link, more than
90% of the traffic is Web, of which nearly 75% is encrypted. Compared to
previous studies, this depicts a larger increase in encrypted Web traffic of up
to a 3-to-1 ratio of HTTPS to HTTP. As such, our observations in this study
further reconfirm that traffic shares change with time and can vary greatly
depending on the vantage point studied despite the use of the same generalized
methodology and analyses, which can also be applied to other traffic monitoring
datasets. | | Source: | arXiv, 2201.00142 | | Services: | Forum | Review | PDF | Favorites | |
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