A Multi-Perspective Study of Internet Performance during the COVID-19 Outbreak

Elmokashfi, Ahmed, Arouna, Alfred, Livadariu, Ioana, Mah Rukh, Fida ORCID: 0000-0001-7660-1150, Kvalbein, Amund, Al-Selwi, Anas, Dreibholz, Thomas and Bryhni, Haakon (2021) A Multi-Perspective Study of Internet Performance during the COVID-19 Outbreak. In: Unspecified event. (Unpublished)

Text (Unpublished paper) 11380 Elmokashfi, Arouna, Livadariu, Mah Rukh, Kvalbein, Al-Selwi, Dreibholz and Bryhni (2022) Multi-Perspective-Study.pdf - Draft Version Restricted to Repository staff only Available under License Creative Commons Attribution 4.0. Download (1MB)

Abstract

The rapid spread of the novel corona virus, SARS-CoV-2, has prompted an unprecedented response from governments across the world. A third of the world population have been placed in varying degrees of lockdown, and the Internet has become the primary medium for conducting most businesses and schooling activities. This paper aims to provide a multi prospective account of Internet performance during the first wave of the pandemic. We investigate the performance of the Internet control plane and data plane from a number of globally spread vantage points. We also look closer at two case studies. First, we look at growth in video traffic during the pandemic, using traffic logs from a global video conferencing provider. Second, we leverage a country-wide deployment of measurement probes to assess the performance of mobile networks during the outbreak. We find that the lockdown has visibly impacted almost all aspects of Internet performance. Access networks have experienced an increase in peak and off-peak end to end latency. Mobile networks exhibit significant changes in download speed, while certain types of video traffic has increased by an order of magnitude. Despite these changes, the Internet seems to have coped reasonably well with the lockdown traffic.

Item Type:	Conference or Workshop Item (Paper)
Article Type:	Article
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Mah Rukh
Date Deposited:	01 Sep 2022 09:54
Last Modified:	03 Nov 2023 14:16
URI:	https://eprints.glos.ac.uk/id/eprint/11380

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