Robust Complex Event Pattern Detection over Streams

Event stream processing (ESP) has become increasingly important in modern applications. In this dissertation, I focus on providing a robust ESP solution by meeting three major research challenges regarding the robustness of ESP systems: (1) while event constraint of the input stream is available, ap...

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Bibliographic Details
Main Author: Li, Ming
Other Authors: Murali Mani, Advisor
Format: Others
Published: Digital WPI 2010
Subjects:
CEP
Online Access:https://digitalcommons.wpi.edu/etd-dissertations/90
https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=1089&context=etd-dissertations
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spelling ndltd-wpi.edu-oai-digitalcommons.wpi.edu-etd-dissertations-10892019-03-22T05:44:11Z Robust Complex Event Pattern Detection over Streams Li, Ming Event stream processing (ESP) has become increasingly important in modern applications. In this dissertation, I focus on providing a robust ESP solution by meeting three major research challenges regarding the robustness of ESP systems: (1) while event constraint of the input stream is available, applying such semantic information in the event processing; (2) handling event streams with out-of-order data arrival and (3) handling event streams with interval-based temporal semantics. The following are the three corresponding research tasks completed by the dissertation: Task I - Constraint-Aware Complex Event Pattern Detection over Streams. In this task, a framework for constraint-aware pattern detection over event streams is designed, which on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism and adjusts the processing strategy dynamically by producing early feedback, releasing unnecessary system resources and terminating corresponding pattern monitor. Task II - Complex Event Pattern Detection over Streams with Out-of-Order Data Arrival. In this task, a mechanism to address the problem of processing event queries specified over streams that may contain out-of-order data is studied, which provides new physical implementation strategies for the core stream algebra operators such as sequence scan, pattern construction and negation filtering. Task III - Complex Event Pattern Detection over Streams with Interval-Based Temporal Semantics. In this task, an expressive language to represent the required temporal patterns among streaming interval events is introduced and the corresponding temporal operator ISEQ is designed. 2010-04-04T07:00:00Z text application/pdf https://digitalcommons.wpi.edu/etd-dissertations/90 https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=1089&context=etd-dissertations Doctoral Dissertations (All Dissertations, All Years) Digital WPI Murali Mani, Advisor Elke A. Rundensteiner, Committee Member Daniel J. Dougherty, Committee Member Tao Lin, Committee Member event stream constraint database CEP interval pattern detection query processing
collection NDLTD
format Others
sources NDLTD
topic event
stream
constraint
database
CEP
interval
pattern detection
query processing
spellingShingle event
stream
constraint
database
CEP
interval
pattern detection
query processing
Li, Ming
Robust Complex Event Pattern Detection over Streams
description Event stream processing (ESP) has become increasingly important in modern applications. In this dissertation, I focus on providing a robust ESP solution by meeting three major research challenges regarding the robustness of ESP systems: (1) while event constraint of the input stream is available, applying such semantic information in the event processing; (2) handling event streams with out-of-order data arrival and (3) handling event streams with interval-based temporal semantics. The following are the three corresponding research tasks completed by the dissertation: Task I - Constraint-Aware Complex Event Pattern Detection over Streams. In this task, a framework for constraint-aware pattern detection over event streams is designed, which on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism and adjusts the processing strategy dynamically by producing early feedback, releasing unnecessary system resources and terminating corresponding pattern monitor. Task II - Complex Event Pattern Detection over Streams with Out-of-Order Data Arrival. In this task, a mechanism to address the problem of processing event queries specified over streams that may contain out-of-order data is studied, which provides new physical implementation strategies for the core stream algebra operators such as sequence scan, pattern construction and negation filtering. Task III - Complex Event Pattern Detection over Streams with Interval-Based Temporal Semantics. In this task, an expressive language to represent the required temporal patterns among streaming interval events is introduced and the corresponding temporal operator ISEQ is designed.
author2 Murali Mani, Advisor
author_facet Murali Mani, Advisor
Li, Ming
author Li, Ming
author_sort Li, Ming
title Robust Complex Event Pattern Detection over Streams
title_short Robust Complex Event Pattern Detection over Streams
title_full Robust Complex Event Pattern Detection over Streams
title_fullStr Robust Complex Event Pattern Detection over Streams
title_full_unstemmed Robust Complex Event Pattern Detection over Streams
title_sort robust complex event pattern detection over streams
publisher Digital WPI
publishDate 2010
url https://digitalcommons.wpi.edu/etd-dissertations/90
https://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=1089&context=etd-dissertations
work_keys_str_mv AT liming robustcomplexeventpatterndetectionoverstreams
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