TCAM-conscious algorithms for data streams

Nagender Bandi, Ahmed Metwally, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently, there has been significant interest in developing space and time efficient solutions for answering continuous summarization queries over data streams. While these techniques are evaluated in a standard CPU setting, many of their applications such as click-fraud detection, and network-traffic summarization typically execute on special networking architectures called Network Processing Units (NPUs). These NPUs interface with special kind of associative memories known as the Ternary Content Addressable Memories (TCAMs). In this paper, we describe how the integrated architecture of NPU and TCAMs can be exploited towards achieving the goal of developing high-speed stream summarization solutions. We analyze popular solutions for the frequent elements problem in data stream, discuss the bottleneck issues and motivate how TCAMs can help alleviate these bottlenecks. A preliminary evaluation on an NPU platform reveals the performance gains of the TCAM-conscious techniques over software implementations.

Original languageEnglish
Title of host publication23rd International Conference on Data Engineering, ICDE 2007
Pages1342-1344
Number of pages3
DOIs
Publication statusPublished - 24 Sep 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: 15 Apr 200720 Apr 2007

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other23rd International Conference on Data Engineering, ICDE 2007
CountryTurkey
CityIstanbul
Period15/4/0720/4/07

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Bandi, N., Metwally, A., Agrawal, D., & El Abbadi, A. (2007). TCAM-conscious algorithms for data streams. In 23rd International Conference on Data Engineering, ICDE 2007 (pp. 1342-1344). [4221797] (Proceedings - International Conference on Data Engineering). https://doi.org/10.1109/ICDE.2007.369007