“Is my Internet down?”: Sifting through User-Affecting Outages with Google Trends
dc.contributor.author
Kirci, Ege Cem
dc.contributor.author
Vahlensieck, Martin
dc.contributor.author
Vanbever, Laurent
dc.date.accessioned
2022-11-28T07:29:54Z
dc.date.available
2022-11-19T04:10:53Z
dc.date.available
2022-11-25T13:09:58Z
dc.date.available
2022-11-25T13:47:10Z
dc.date.available
2022-11-28T07:29:54Z
dc.date.issued
2022-10
dc.identifier.isbn
978-1-4503-9259-4
en_US
dc.identifier.other
10.1145/3517745.3561428
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/581815
dc.description.abstract
What are the worst outages for Internet users? How long do they last, and how wide are they? Such questions are hard to answer via traditional outage detection and analysis techniques, as they conventionally rely on network-level signals and do not necessarily represent users’ perceptions of connectivity. We present SIFT, a detection and analysis tool for capturing user-affecting Internet outages. SIFT leverages users’ aggregated web search activity to detect outages. Specifically, SIFT starts by building a timeline of users’ interests in outage-related search queries. It then analyzes this timeline looking for spikes of user interest. Finally, SIFT characterizes these spikes in duration, geographical extent, and simultaneously trending search terms which may help understand root causes, such as power outages or associated ISPs. We use SIFT to collect more than 49 000 Internet outages in the United States over the last two years. Among others, SIFT reveals that user-affecting outages: (i) do not happen uniformly: half of them originate from 10 states only; (ii) can affect users for a long time: 10% of them last at least 3 hours; and (iii) can have a broad impact: 11% of them simultaneously affect at least 10 distinct states. SIFT annotations also reveal a perhaps overlooked fact: outages are often caused by climate and/or power-related issues.
en_US
dc.language.iso
en
en_US
dc.publisher
Association for Computing Machinery
en_US
dc.subject
Internet outages
en_US
dc.subject
Anomaly detection
en_US
dc.subject
Data mining
en_US
dc.subject
Google Trends
en_US
dc.title
“Is my Internet down?”: Sifting through User-Affecting Outages with Google Trends
en_US
dc.type
Conference Paper
dc.date.published
2022-10-25
ethz.book.title
IMC '22: Proceedings of the 22nd ACM Internet Measurement Conference
en_US
ethz.pages.start
290
en_US
ethz.pages.end
297
en_US
ethz.event
22nd ACM Internet Measurement Conference (IMC 2022)
en_US
ethz.event.location
Nice, France
en_US
ethz.event.date
October 25-27, 2022
en_US
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02640 - Inst. f. Technische Informatik und Komm. / Computer Eng. and Networks Lab.::09477 - Vanbever, Laurent / Vanbever, Laurent
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02640 - Inst. f. Technische Informatik und Komm. / Computer Eng. and Networks Lab.::09477 - Vanbever, Laurent / Vanbever, Laurent
ethz.date.deposited
2022-11-19T04:10:55Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-11-28T07:29:55Z
ethz.rosetta.lastUpdated
2024-02-02T19:01:20Z
ethz.rosetta.versionExported
true
ethz.COinS
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