Trinocular: Understanding Internet Reliability Through Adaptive Probing

Trinocular: Understanding Internet Reliability Through Adaptive Probing

Quan, Lin and Heidemann, John and Pradkin, Yuri
USC/Information Sciences Institute

Lin Quan, John Heidemann and Yuri Pradkin 2013. Trinocular: Understanding Internet Reliability Through Adaptive Probing. Proceedings of the ACM SIGCOMM Conference (Hong Kong, China, Aug. 2013), 255–266.

Abstract

Natural and human factors cause Internet outages—from big events like Hurricane Sandy in 2012 and the Egyptian Internet shutdown in Jan.%7e2011 to small outages every day that go unpublicized. We describe \emphTrinocular, an outage detection system that uses active probing to understand reliability of edge networks. Trinocular is \emphprincipled: deriving a simple model of the Internet that captures the information pertinent to outages, and populating that model through long-term data, and learning current network state through ICMP probes. It is \emphparsimonious, using Bayesian inference to determine how many probes are needed. On average, each Trinocular instance sends fewer than 20 probes per hour to each /24 network block under study, increasing Internet “background radiation” by less than 0.7%. Trinocular is also \emphpredictable and \emphprecise: we provide known precision in outage timing and duration. Probing in \emphrounds of 11 minutes, we detect 100% of outages one round or longer, and estimate outage duration within one-half round. Since we require little traffic, a single machine can track 3.4M /24 IPv4 blocks, all of the Internet currently suitable for analysis. We show that our approach is \emphsignificantly more accurate than the best current methods, with about one-third fewer false conclusions, and about 30% greater coverage at constant accuracy. We validate our approach using controlled experiments, use Trinocular to analyze two days of Internet outages observed from three sites, and re-analyze three years of existing data to develop trends for the Internet.

Reference

@inproceedings{Quan13c,
  author = {Quan, Lin and Heidemann, John and Pradkin, Yuri},
  title = {Trinocular: Understanding Internet Reliability Through Adaptive Probing},
  booktitle = {Proceedings of the  ACM SIGCOMM Conference },
  year = {2013},
  sortdate = {2013-08-01},
  pages = {255--266},
  month = aug,
  address = {Hong Kong, China},
  publisher = {ACM},
  location = {johnh: pafile},
  keywords = {internet outage detection, hurricane sandy,
                    bayesian inference},
  copyrightholder = {ACM},
  copyrightterms = {
  	Permission to make digital or hard
   	copies of portions of this work for personal or
   	classroom use is granted without fee provided that
   	the copies are not made or distributed for profit or
   	commercial advantage and that copies bear this
   	notice and the full citation on the first page in
   	print or the first screen in digital
   	media. Copyrights for components of this work owned
   	by others than ACM must be honored. Abstracting with
   	credit is permitted. 
   	otherwise, to republish, to post on servers, or to
   	redistribute to lists, requires prior specific
   	permission and/or a fee. Send written requests for
   	republication to ACM Publications, Copyright &
   	Permissions at the address above or fax +1 (212)
   	869-0481 or email permissions@acm.org.},
  url = {http://www.isi.edu/%7ejohnh/PAPERS/Quan13c.html},
  pdfurl = {http://www.isi.edu/%7ejohnh/PAPERS/Quan13c.pdf},
  myorganization = {USC/Information Sciences Institute},
  doi = {http://doi.acm.org/10.1145/2486001.2486017},
  project = {ant, lacrend, duoi}
}

Copyright

Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org.