@InProceedings{Bogutz19a,
        author =        "Ryan Bogutz and Yuri Pradkin and John Heidemann",
        title =         "Identifying Important Internet Outages",
        booktitle =     "Sixth National Symposium for NSF REU Research in Data Science, Systems, and Security",
        year =          "2019",
	sortdate = 		"2019-12-12", 
	project = "ant, lacanic, divoice, iiovadr, isireu, reu",
	jsubject = "routing",
	month =		dec,
	jlocation =	"johnh: pafile",
	keywords =	"network outage detection, reporting",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.pdf",
	blogurl = "https://ant.isi.edu/blog/?p=1376",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "Today, outage detection systems can track outages across the whole
IPv4 Internet---millions of networks.  However, it becomes difficult
to find meaningful, interesting events in this huge dataset, since
three months of data can easily include 660M observations and
thousands of outage events.  We propose
an \emph{outage reporting system} that sifts through this data
to find the most \emph{interesting} events.
We explore multiple metrics to evaluate
``interesting'', reflecting the size and severity of outages.  We show
that defining interest as the product of size by severity works well,
avoiding degenerate cases like complete outages affecting a few
people, and apparently large outages that affect only a small fraction
of people in an area.  We have integrated outage reporting into our
existing public website (\url{https://outage.ant.isi.edu}) with the
goal of making near-real-time outage information accessible to the
general public.  Such data can help answer questions like ``what are
the most significant outages today?'', ``did Flordia have major
problems in an ongoing hurricane?'', and ``are there power outages in
Venezuela?''.",
}

{"_id":"c96dxTLzyjnhchzmk","bibbaseid":"bogutz-pradkin-heidemann-identifyingimportantinternetoutages-2019","author_short":["Bogutz, R.","Pradkin, Y.","Heidemann, J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Ryan"],"propositions":[],"lastnames":["Bogutz"],"suffixes":[]},{"firstnames":["Yuri"],"propositions":[],"lastnames":["Pradkin"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]}],"title":"Identifying Important Internet Outages","booktitle":"Sixth National Symposium for NSF REU Research in Data Science, Systems, and Security","year":"2019","sortdate":"2019-12-12","project":"ant, lacanic, divoice, iiovadr, isireu, reu","jsubject":"routing","month":"December","jlocation":"johnh: pafile","keywords":"network outage detection, reporting","url":"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.html","pdfurl":"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.pdf","blogurl":"https://ant.isi.edu/blog/?p=1376","myorganization":"USC/Information Sciences Institute","copyrightholder":"authors","abstract":"Today, outage detection systems can track outages across the whole IPv4 Internet—millions of networks. However, it becomes difficult to find meaningful, interesting events in this huge dataset, since three months of data can easily include 660M observations and thousands of outage events. We propose an \\emphoutage reporting system that sifts through this data to find the most \\emphinteresting events. We explore multiple metrics to evaluate ``interesting'', reflecting the size and severity of outages. We show that defining interest as the product of size by severity works well, avoiding degenerate cases like complete outages affecting a few people, and apparently large outages that affect only a small fraction of people in an area. We have integrated outage reporting into our existing public website (˘rlhttps://outage.ant.isi.edu) with the goal of making near-real-time outage information accessible to the general public. Such data can help answer questions like ``what are the most significant outages today?'', ``did Flordia have major problems in an ongoing hurricane?'', and ``are there power outages in Venezuela?''.","bibtex":"@InProceedings{Bogutz19a,\n author = \"Ryan Bogutz and Yuri Pradkin and John Heidemann\",\n title = \"Identifying Important Internet Outages\",\n booktitle = \"Sixth National Symposium for NSF REU Research in Data Science, Systems, and Security\",\n year = \"2019\",\n\tsortdate = \t\t\"2019-12-12\", \n\tproject = \"ant, lacanic, divoice, iiovadr, isireu, reu\",\n\tjsubject = \"routing\",\n\tmonth =\t\tdec,\n\tjlocation =\t\"johnh: pafile\",\n\tkeywords =\t\"network outage detection, reporting\",\n\turl =\t\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.html\",\n\tpdfurl =\t\"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.pdf\",\n\tblogurl = \"https://ant.isi.edu/blog/?p=1376\",\n\tmyorganization =\t\"USC/Information Sciences Institute\",\n\tcopyrightholder = \"authors\",\n\tabstract = \"Today, outage detection systems can track outages across the whole\nIPv4 Internet---millions of networks. However, it becomes difficult\nto find meaningful, interesting events in this huge dataset, since\nthree months of data can easily include 660M observations and\nthousands of outage events. We propose\nan \\emph{outage reporting system} that sifts through this data\nto find the most \\emph{interesting} events.\nWe explore multiple metrics to evaluate\n``interesting'', reflecting the size and severity of outages. We show\nthat defining interest as the product of size by severity works well,\navoiding degenerate cases like complete outages affecting a few\npeople, and apparently large outages that affect only a small fraction\nof people in an area. We have integrated outage reporting into our\nexisting public website (\\url{https://outage.ant.isi.edu}) with the\ngoal of making near-real-time outage information accessible to the\ngeneral public. Such data can help answer questions like ``what are\nthe most significant outages today?'', ``did Flordia have major\nproblems in an ongoing hurricane?'', and ``are there power outages in\nVenezuela?''.\",\n}\n\n","author_short":["Bogutz, R.","Pradkin, Y.","Heidemann, J."],"bibbaseid":"bogutz-pradkin-heidemann-identifyingimportantinternetoutages-2019","role":"author","urls":{"Paper":"https://ant.isi.edu/%7ejohnh/PAPERS/Bogutz19a.html"},"keyword":["network outage detection","reporting"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["network outage detection","reporting"],"search_terms":["identifying","important","internet","outages","bogutz","pradkin","heidemann"],"title":"Identifying Important Internet Outages","year":2019}