Independent counter estimation buckets

Gil Einziger, Benny Fellman, Yaron Kassner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations


Measurement capabilities are essential for a variety of network applications, such as load balancing, routing, fairness and intrusion detection. These capabilities require large counter arrays in order to monitor the traffic of all network flows. While commodity SRAM memories are capable of operating at line speed, they are too small to accommodate large counter arrays. Previous works suggested estimators, which trade precision for reduced space. However, in order to accurately estimate the largest counter, these methods compromise the accuracy of the rest of the counters. In this work we present a closed form representation of the optimal estimation function. We then introduce Independent Counter Estimation Buckets (ICE-Buckets), a novel algorithm that improves estimation accuracy for all counters. This is achieved by separating the flows to buckets and configuring the optimal estimation function according to each bucket's counter scale. We prove an improved upper bound on the relative error and demonstrate an accuracy improvement of up to 57 times on real Internet packet traces.

Original languageEnglish
Title of host publication2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781479983810
StatePublished - 21 Aug 2015
Externally publishedYes
Event34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015 - Hong Kong, Hong Kong
Duration: 26 Apr 20151 May 2015

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
Country/TerritoryHong Kong
CityHong Kong

ASJC Scopus subject areas

  • Computer Science (all)
  • Electrical and Electronic Engineering


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