Paper by Erik D. Demaine

Reference:

Erik D. Demaine, Alejandro López-Ortiz, and J. Ian Munro, “Frequency Estimation of Internet Packet Streams with Limited Space”, in Proceedings of the 10th Annual European Symposium on Algorithms (ESA 2002), Lecture Notes in Computer Science, volume 2461, Rome, Italy, September 17–21, 2002, pages 348–360.

BibTeX

@InProceedings{NetworkStats_ESA2002,
  AUTHOR        = {Erik D. Demaine and Alejandro L\'opez-Ortiz and J. Ian Munro},
  TITLE         = {Frequency Estimation of Internet Packet Streams with Limited Space},
  BOOKTITLE     = {Proceedings of the 10th Annual European Symposium on Algorithms (ESA 2002)},
  BOOKURL       = {http://www.dis.uniroma1.it/~algo02/esa02/},
  SERIES        = {Lecture Notes in Computer Science},
  SERIESURL     = {http://www.springer.de/comp/lncs/},
  VOLUME        = 2461,
  ADDRESS       = {Rome, Italy},
  MONTH         = {September 17--21},
  YEAR          = 2002,
  PAGES         = {348--360},

  copyright     = {The paper is \copyright Springer-Verlag.},
  length        = {12 pages},
  papers        = {NetworkStats_TR2002},
  doi           = {https://dx.doi.org/10.1007/3-540-45749-6_33},
  dblp          = {https://dblp.org/rec/conf/esa/DemaineLM02},
  comments      = {This paper is also available from <A HREF="https://doi.org/10.1007/3-540-45749-6_33">SpringerLink</A>.},
  updates       = {Our deterministic algorithm is identical to an earlier
                   algorithm of J. Misra and D. Gries, &ldquo;Finding repeated
                   elements&rdquo;, <I>Science of Programming</I>,
                   2:143&ndash;152, 1982.},
}

Abstract:

We consider a router on the Internet analyzing the statistical properties of a TCP/IP packet stream. A fundamental difficulty with measuring traffic behavior on the Internet is that there is simply too much data to be recorded for later analysis, on the order of gigabytes a second. As a result, network routers can collect only relatively few statistics about the data. The central problem addressed here is to use the limited memory of routers to determine essential features of the network traffic stream. A particularly difficult and representative subproblem is to determine the top k categories to which the most packets belong, for a desired value of k and for a given notion of categorization such as the destination IP address.

We present an algorithm that deterministically finds (in particular) all categories having a frequency above 1/(m+1) using m counters, which we prove is best possible in the worst case. We also present a sampling-based algorithm for the case that packet categories follow an arbitrary distribution, but their order over time is permuted uniformly at random. Under this model, our algorithm identifies flows above a frequency threshold of roughly 1/√n m with high probability, where m is the number of counters and n is the number of packets observed. This guarantee is not far off from the ideal of identifying all flows (probability 1/n), and we prove that it is best possible up to a logarithmic factor. We show that the algorithm ranks the identified flows according to frequency within any desired constant factor of accuracy.

Comments:

This paper is also available from SpringerLink.

Updates:

Our deterministic algorithm is identical to an earlier algorithm of J. Misra and D. Gries, “Finding repeated elements”, Science of Programming, 2:143–152, 1982.

Copyright:

The paper is \copyright Springer-Verlag.

Length:

The paper is 12 pages.

Availability:

The paper is available in PostScript (161k), gzipped PostScript (65k), and PDF (143k).

See information on file formats.

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Related papers:

NetworkStats_TR2002 (Frequency Estimation of Internet Packet Streams with Limited Space)