Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states

Sam Sengupta; B. Andriamanalimanana; S. W. Card; Kaustav Das; Rachita Sharma; Anitha Gunasekaran

doi:10.1109/IDAACS.2003.1249549

Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states

Sam Sengupta
, B. Andriamanalimanana
, S. W. Card
, Kaustav Das
, Rachita Sharma
, Anitha Gunasekaran

College of Engineering

SUNY Polytechnic Institute

SUNY Polytechnic Institute
Critical Technologies Inc.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Mining a high speed bursty data stream is always a challenge on a limited size buffer. Often a relatively cheaper AMS (anytime mining solution) approach may be the only plausible scheme one could rely on at times. Mining task becomes enormously complicated when the first-level buffer has to host several dependent streams. This becomes worse when incoming data streams take time to settle down in their respective steady states. A buffer sharing and capture models are indicated for some simple situations involving multiple streams. These models could be extended to generalize a linear buffer model to a hierarchical model.

Original language	English
Title of host publication	Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems
Subtitle of host publication	Technology and Applications, IDAACS 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	201-204
Number of pages	4
ISBN (Electronic)	0780381386, 9780780381384
DOIs	https://doi.org/10.1109/IDAACS.2003.1249549
State	Published - 2003
Event	2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003 - Lviv, Ukraine Duration: Sep 8 2003 → Sep 10 2003

Publication series

Name	Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003

Conference

Conference	2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003
Country/Territory	Ukraine
City	Lviv
Period	09/8/03 → 09/10/03

Keywords

Buffer storage
Data mining
Databases
Internet
Knowledge engineering
Sampling methods
Stationary state

Access to Document

10.1109/IDAACS.2003.1249549

Cite this

Sengupta, S., Andriamanalimanana, B., Card, S. W., Das, K., Sharma, R., & Gunasekaran, A. (2003). Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states. In Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003 (pp. 201-204). Article 1249549 (Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IDAACS.2003.1249549

Sengupta, Sam ; Andriamanalimanana, B. ; Card, S. W. et al. / Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states. Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 201-204 (Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003).

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title = "Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states",

abstract = "Mining a high speed bursty data stream is always a challenge on a limited size buffer. Often a relatively cheaper AMS (anytime mining solution) approach may be the only plausible scheme one could rely on at times. Mining task becomes enormously complicated when the first-level buffer has to host several dependent streams. This becomes worse when incoming data streams take time to settle down in their respective steady states. A buffer sharing and capture models are indicated for some simple situations involving multiple streams. These models could be extended to generalize a linear buffer model to a hierarchical model.",

keywords = "Buffer storage, Data mining, Databases, Internet, Knowledge engineering, Sampling methods, Stationary state",

author = "Sam Sengupta and B. Andriamanalimanana and Card, \{S. W.\} and Kaustav Das and Rachita Sharma and Anitha Gunasekaran",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003 ; Conference date: 08-09-2003 Through 10-09-2003",

year = "2003",

doi = "10.1109/IDAACS.2003.1249549",

language = "English",

series = "Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003",

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Sengupta, S, Andriamanalimanana, B, Card, SW, Das, K, Sharma, R & Gunasekaran, A 2003, Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states. in Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003., 1249549, Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003, Institute of Electrical and Electronics Engineers Inc., pp. 201-204, 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003, Lviv, Ukraine, 09/8/03. https://doi.org/10.1109/IDAACS.2003.1249549

Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states. / Sengupta, Sam; Andriamanalimanana, B.; Card, S. W. et al.
Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 201-204 1249549 (Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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KW - Knowledge engineering

KW - Sampling methods

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BT - Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems

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Sengupta S, Andriamanalimanana B, Card SW, Das K, Sharma R, Gunasekaran A. Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states. In Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 201-204. 1249549. (Proceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003). doi: 10.1109/IDAACS.2003.1249549

Data mining a high-speed bursty stream on a limited buffer in pseudo-stationary states

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