When the Internet Sleeps: Correlating Diurnal Networks With External Factors (extended). Quan, L., Heidemann, J., & Pradkin, Y. Technical Report ISI-TR-2014-691b, USC/Information Sciences Institute, May, 2014. (updated August 2014)
When the Internet Sleeps: Correlating Diurnal Networks With External Factors (extended) [link]Paper  abstract   bibtex   
As the Internet matures, policy questions loom larger in its operation. When should an ISP, city, or government invest in infrastructure? How do their policies affect use? In this work, we develop a new approach to evaluate how policies, economic conditions and technology correlates with Internet use around the world. First, we develop an adaptive and accurate approach to estimate \emphblock availability, the fraction of active IP addresses in each /24 block over short timescales (every 11 minutes). Our estimator provides a new lens to interpret data taken from existing long-term outage measurements, this requiring no no additional traffic. (If new collection was required, it would be lightweight, since on average, outage detection requires less than 20 probes per hour per /24 block; less than 1% of background radiation.) Second, we show that spectral analysis of this measure can identify \emphdiurnal usage: blocks where addresses are regularly used during part of the day and idle in other times. Finally, we analyze data for the entire responsive Internet (3.7M /24 blocks) over 35 days. These global observations show \emphwhen and \emphwhere the Internet sleeps—networks are mostly always-on in the US and Western Europe, and diurnal in much of Asia, South America, and Eastern Europe. ANOVA testing shows that diurnal networks correlate negatively with country GDP and electrical consumption, quantifying that national policies and economics relate to networks.
@TechReport{Quan14b,
	author = 	"Lin Quan and John Heidemann and Yuri Pradkin",
	title = 	"When the {Internet} Sleeps: Correlating
                  Diurnal Networks With External Factors (extended)" ,
	institution = 	"USC/Information Sciences Institute",
	year = 		2014,
	sortdate = "2014-05-01",
	project = "ant, lacrend, retrofuture, duoi",
	jsubject = "routing",
	number = 	"ISI-TR-2014-691b",
	month = 	may,
	note = "(updated August 2014)",
	jlocation = 	"johnh: pafile",
	keywords = 	"routing outage detection, diurnal network
                  behavior, active probing,
                  ntework outages",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Quan14b.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Quan14b.pdf",
	otherurl =	"ftp://ftp.isi.edu/isi-pubs/tr-699b.pdf",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "
As the Internet matures, policy questions loom larger in its
operation.  When should an ISP, city, or government invest in
infrastructure?  How do their policies affect use?  In this work, we
develop a new approach to evaluate how policies, economic conditions
and technology correlates with Internet use around the world.  First,
we develop an adaptive and accurate approach to estimate \emph{block
  availability}, the fraction of active IP addresses in each /24 block
over short timescales (every 11 minutes).  Our estimator provides a
new lens to interpret data taken from existing long-term outage
measurements, this requiring no no additional traffic.  (If new
collection was required, it would be lightweight, since on average,
outage detection requires less than 20 probes per hour per /24 block;
less than 1\% of background radiation.)  Second, we show that spectral
analysis of this measure can identify \emph{diurnal usage}: blocks
where addresses are regularly used during part of the day and idle in
other times.  Finally, we analyze data for the entire responsive
Internet (3.7M /24 blocks) over 35 days.  These global observations
show \emph{when} and \emph{where} the Internet sleeps---networks are
mostly always-on in the US and Western Europe, and diurnal in much of
Asia, South America, and Eastern Europe.  ANOVA testing shows that
diurnal networks correlate negatively with country GDP and electrical
consumption, quantifying that national policies and economics relate
to networks.
",
}

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