Massive internet outages5/21/2023 In 3rd Workshop on Online Social Networks (WOSN 2010). Measuring Online Service Availability Using Twitter. Marti Motoyama, Brendan Meeder, Kirill Levchenko, Geoffrey M Voelker, and Stefan Savage.What Led to Internet Outage That Took down Some Major Websites on July 22? Check out Why. Building a Real-Time Internet Outage Detection System with Flink Fing | LinkedIn. Springer International Publishing, Cham, 247-265. In Passive and Active Measurement, Oliver Hohlfeld, Andra Lutu, and Dave Levin (Eds.). On the Resilience of Internet Infrastructures in Pacific Northwest to Earthquakes. Juno Mayer, Valerie Sahakian, Emilie Hooft, Douglas Toomey, and Ramakrishnan Durairajan.GeoIP® Databases & Services: Industry Leading IP Intelligence. Andrew Kirmse's Page - Topographic Prominence. Web Queries as a Source for Syndromic Surveillance. Anette Hulth, Gustaf Rydevik, and Annika Linde.Severed Power Line Causing Water Outages and Issues in Colorado City. Association for Computing Machinery, New York, NY, USA, 169-182. In Proceedings of the 8th ACM SIGCOMM Conference on Internet Measurement (IMC '08). Census and Survey of the Visible Internet. John Heidemann, Yuri Pradkin, Ramesh Govindan, Christos Papadopoulos, Genevieve Bartlett, and Joseph Bannister.Massive Pacific Northwest Storm Causes Power Outages, Downed Trees. Major Internet Outage: Dozens of Websites and Apps Were Down. Proceedings of the National Academy of Sciences 107, 41 (Oct. Predicting Consumer Behavior with Web Search. Detecting Influenza Epidemics Using Search Engine Query Data. Outages Spike in Late April as COVID-19 Trends Strain Internet. How Texas' Power Grid Failed in 2021 - and Who's Responsible for Preventing a Repeat. Mandi Cai Ferman, Erin Douglas and Mitchell.Infodemiology: Tracking Flu-Related Searches on the Web for Syndromic Surveillance. Google 'overwhelmingly' Dominates Search Market, Antitrust Committee States. Comcast Xfinity Internet Outage Hits Customers across the US. About Us | We Detect When Technology Fails. Storms Leave 600,000+ Michiganders without Power Flash Flood Warning in Wayne County. Zhi Da, Joseph Engelberg, and Pengjie Gao.US: Tropical Storm Zeta Causes Disruptions in Georgia October 29 /Update 4. Predicting the Present with Google Trends. Social Science Research Network, Rochester, NY. Predicting Initial Claims for Unemployment Benefits. Charge Your Power Banks: Rotating Blackouts and Power Shutoffs Possible In Parts of Bay Area This Week. Several Schools Closed as Thousands Remain without Power. Thousands Still without Power in Kentucky Following Devastating Tornado Outbreak. Journal of Network and Computer Applications 113 (2018), 36-63. A Comprehensive Survey on Internet Outages. Giuseppe Aceto, Alessio Botta, Pietro Marchetta, Valerio Persico, and Antonio Pescapé.SIFT annotations also reveal a perhaps overlooked fact: outages are often caused by climate and/or power-related issues. 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. We use SIFT to collect more than 49 000 Internet outages in the United States over the last two years. 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. It then analyzes this timeline looking for spikes of user interest. Specifically, SIFT starts by building a timeline of users' interests in outage-related search queries. SIFT leverages users' aggregated web search activity to detect outages. We present SIFT, a detection and analysis tool for capturing user-affecting Internet outages. 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.
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