Elke A. Rundensteiner
Daniel J. Dougherty
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.
Worcester Polytechnic Institute
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Li, M. (2010). Robust Complex Event Pattern Detection over Streams. Retrieved from https://digitalcommons.wpi.edu/etd-dissertations/90
event, stream, constraint, database, CEP, interval, pattern detection, query processing