License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.KiVS.2011.133
URN: urn:nbn:de:0030-drops-29648
Go to the corresponding OASIcs Volume Portal

Marold, Alexander ; Lieven, Peter ; Scheuermann, Björn

Distributed Probabilistic Network Traffic Measurements

12.pdf (1 MB)


Measuring the per-flow traffic in large networks is very challenging due to the high performance requirements on the one hand, and due to the necessity to merge locally recorded data from multiple routers in order to obtain network-wide statistics on the other hand. The latter is nontrivial because traffic that traversed more than one measurement point must only be counted once, which requires duplicate-insensitive distributed counting mechanisms. Sampling-based traffic accounting as implemented in today’s routers results in large approximation errors, and does not allow for merging information from multiple points in the network into network-wide total traffic statistics. Here, we present Distributed Probabilistic Counting (DPC), an algorithm to obtain duplicate-insensitive distributed per-flow traffic statistics based on a probabilistic counting technique. DPC is structurally simple, very fast, and highly parallelizable, and therefore allows for efficient implementations in software and hardware. At the same time it provides very accurate traffic statistics, as we demonstrate based on both artificial and real-world traffic data.

BibTeX - Entry

  author =	{Alexander Marold and Peter Lieven and Bj{\"o}rn Scheuermann},
  title =	{{Distributed Probabilistic Network Traffic Measurements}},
  booktitle =	{17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011) },
  pages =	{133--144},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-27-9},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{17},
  editor =	{Norbert Luttenberger and Hagen Peters},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-29648},
  doi =		{10.4230/OASIcs.KiVS.2011.133},
  annote =	{Keywords: network measurement, flow monitoring, probabilistic techniques}

Keywords: network measurement, flow monitoring, probabilistic techniques
Collection: 17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011)
Issue Date: 2011
Date of publication: 25.02.2011

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI