High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources

This paper presents a novel data structure, called Event-centric Composable Queue (ECQ), a basic building block of a new scalable composite event monitoring (CEM) framework, SCEMon. In particular, we focus on the scalability issues when large numbers of CEM queries and event sources exist in upcomin...

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Main Authors: LEE, SangJeong, LEE, Youngki, KIM, Byoungjip, CANDAN, K. Selcuk, RHEE, Yunseok, SONG, Junehwa
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Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/2081
https://ink.library.smu.edu.sg/context/sis_research/article/3080/viewcontent/p137_lee.pdf
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spelling sg-smu-ink.sis_research-30802016-11-08T09:32:05Z High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources LEE, SangJeong LEE, Youngki KIM, Byoungjip CANDAN, K. Selcuk RHEE, Yunseok SONG, Junehwa This paper presents a novel data structure, called Event-centric Composable Queue (ECQ), a basic building block of a new scalable composite event monitoring (CEM) framework, SCEMon. In particular, we focus on the scalability issues when large numbers of CEM queries and event sources exist in upcoming CEM environments. To address these challenges effectively, we take an event-centric sharing approach rather than dealing with queries and sources separately. ECQ is a shared queue, which stores incoming event instances of a primitive event class. ECQs are designed to facilitate efficient shared evaluations of multiple queries over very large volumes of event streams from numerous event sources. ECQs are composable and form a single shared network within which multiple queries are simultaneously evaluated. In this paper, we present efficient shared processing techniques operating on top of the proposed shared ECQ network. The performance evaluation shows that the proposed approach achieves a high level of scalability compared to conventional separate processing approaches in large-scale CEM environments. 2011-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2081 info:doi/10.1145/2002259.2002280 https://ink.library.smu.edu.sg/context/sis_research/article/3080/viewcontent/p137_lee.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University composite event monitoring event streams scalable processing Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic composite event monitoring
event streams
scalable processing
Software Engineering
spellingShingle composite event monitoring
event streams
scalable processing
Software Engineering
LEE, SangJeong
LEE, Youngki
KIM, Byoungjip
CANDAN, K. Selcuk
RHEE, Yunseok
SONG, Junehwa
High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
description This paper presents a novel data structure, called Event-centric Composable Queue (ECQ), a basic building block of a new scalable composite event monitoring (CEM) framework, SCEMon. In particular, we focus on the scalability issues when large numbers of CEM queries and event sources exist in upcoming CEM environments. To address these challenges effectively, we take an event-centric sharing approach rather than dealing with queries and sources separately. ECQ is a shared queue, which stores incoming event instances of a primitive event class. ECQs are designed to facilitate efficient shared evaluations of multiple queries over very large volumes of event streams from numerous event sources. ECQs are composable and form a single shared network within which multiple queries are simultaneously evaluated. In this paper, we present efficient shared processing techniques operating on top of the proposed shared ECQ network. The performance evaluation shows that the proposed approach achieves a high level of scalability compared to conventional separate processing approaches in large-scale CEM environments.
format text
author LEE, SangJeong
LEE, Youngki
KIM, Byoungjip
CANDAN, K. Selcuk
RHEE, Yunseok
SONG, Junehwa
author_facet LEE, SangJeong
LEE, Youngki
KIM, Byoungjip
CANDAN, K. Selcuk
RHEE, Yunseok
SONG, Junehwa
author_sort LEE, SangJeong
title High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
title_short High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
title_full High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
title_fullStr High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
title_full_unstemmed High-Performance Composite Event Monitoring System Supporting Large Numbers of Queries and Sources
title_sort high-performance composite event monitoring system supporting large numbers of queries and sources
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/2081
https://ink.library.smu.edu.sg/context/sis_research/article/3080/viewcontent/p137_lee.pdf
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